Calorie Deficit Formula: Master Your Weight Loss Goals

Calorie calculators can produce different answers even when you enter exactly the same height, weight and age. One reason is the equation used to estimate resting energy expenditure. Two names you will often see are Mifflin-St Jeor and Katch-McArdle.

Both formulas aim to estimate the energy your body needs before your normal daily activity is added, but they take different routes. Mifflin-St Jeor uses body weight, height, age and sex. Katch-McArdle uses lean body mass, which means it depends on having an estimate of body-fat percentage. That difference sounds simple, but it has major practical consequences.

This guide compares the two formulas, shows worked examples, explains when body-fat data helps and when it can make an estimate worse, and gives you a practical way to decide which number to use. You can also calculate your overall daily requirement with The Dryden’s TDEE Calculator.

Quick answer: for most people who do not have a reliable body-composition measurement, Mifflin-St Jeor is the simpler default. Katch-McArdle can be useful when lean body mass is known reasonably well, especially when body composition is unusual, but a formula does not become automatically more accurate just because it includes body fat. Whichever equation you use, treat it as a starting estimate and validate it against real-world trends.

What are BMR and RMR?

Before comparing formulas, it helps to clarify the language. Basal metabolic rate is the energy required to support essential physiological functions under tightly controlled resting conditions. Resting metabolic rate is closely related but is generally measured under slightly less restrictive conditions. In everyday fitness calculators the terms are often used loosely or interchangeably, even though they are not technically identical.

For practical calorie planning, the number is normally used as the resting component of a larger TDEE estimate. A calculator applies an activity factor or otherwise models movement and exercise to estimate maintenance calories. That is why the formula is only one part of the final answer.

The Mifflin-St Jeor formula

The Mifflin-St Jeor equation was published in 1990 and is widely used to estimate resting metabolic rate in adults. The commonly used versions are:

Men: RMR = 10 × weight in kg + 6.25 × height in cm − 5 × age in years + 5

Women: RMR = 10 × weight in kg + 6.25 × height in cm − 5 × age in years − 161

The attraction is obvious: the inputs are easy to obtain. You need a scale, your height and your age. You do not need a body-fat scanner or skinfold assessment.

Mifflin-St Jeor example

Consider a 35-year-old woman who is 165 cm tall and weighs 70 kg:

10 × 70 = 700
6.25 × 165 = 1,031.25
5 × 35 = 175

700 + 1,031.25 − 175 − 161 = 1,395.25 kcal/day.

That is an estimated resting requirement, not a maintenance target. If an activity model subsequently placed her around a 1.55 multiplier, the rough TDEE would be approximately 2,163 calories a day. Both steps contain uncertainty.

The Katch-McArdle formula

Katch-McArdle takes a different approach. A common version is:

RMR/BMR ≈ 370 + (21.6 × lean body mass in kg)

Lean body mass is body weight minus fat mass. If somebody weighs 70 kg and is estimated to be 25% body fat, estimated lean mass is 75% of 70 kg, or 52.5 kg.

Using Katch-McArdle:

370 + (21.6 × 52.5) = 370 + 1,134 = 1,504 kcal/day.

In this example, Katch-McArdle gives a resting estimate about 109 calories higher than the Mifflin result above. Neither number should automatically be declared correct. The accuracy depends partly on how well the equation fits the individual and, for Katch-McArdle, how accurate the body-fat estimate is.

The key difference: body composition

Mifflin-St Jeor treats total body weight as an input. It does not ask how much of that weight is fat mass versus fat-free mass. Katch-McArdle tries to account for that difference by using lean body mass.

That can sound more personalised, particularly for muscular people. However, body-fat measurement is itself an estimate. Smart scales, handheld devices, circumference equations, skinfolds and even more sophisticated methods have different sources of error. If your body-fat estimate is wrong, your lean-mass input is wrong, and the apparent extra precision of Katch-McArdle can become false precision.

Why Mifflin-St Jeor is often a good default

A systematic review comparing common resting metabolic rate equations in non-obese and obese adults found Mifflin-St Jeor to be among the more reliable commonly used equations, although individual error still occurred and some groups were underrepresented. The important point is not that Mifflin is perfect. It is that it has reasonable evidence behind it and requires inputs most people can measure with relatively little error.

That makes it practical for general-population calorie planning. If somebody has no trustworthy body-fat assessment, adding a guessed body-fat percentage to use Katch-McArdle may make the result less dependable rather than more personalised.

When Katch-McArdle may be useful

Katch-McArdle can be informative when you have a reasonably credible estimate of lean mass and your body composition differs substantially from the average person represented by weight-and-height equations. A heavily muscled strength athlete is the obvious example. Two people can share the same scale weight and height while having very different proportions of fat and lean tissue.

It can also be useful as a comparison. If Mifflin-St Jeor and Katch-McArdle produce very similar estimates, that agreement may increase confidence in the general range. If they differ substantially, do not simply choose the result you prefer. Investigate why.

Does Katch-McArdle automatically beat Mifflin for athletes?

No. Research in athletic populations shows that the accuracy of predictive RMR equations varies considerably. A 2023 systematic review and meta-analysis covering many equations in adult athletes found that performance depended on the equation and population, and no single formula was universally superior. This matters because athletes are exactly the group most likely to assume that a lean-mass equation must be best.

Body composition is relevant to metabolism, but the quality of the input measurement, the population used to derive an equation and the individual’s physiology all matter. A formula cannot capture every difference in training history, hormone status, adaptive changes, energy availability or organ mass.

What indirect calorimetry adds

Predictive equations estimate resting expenditure. Indirect calorimetry measures oxygen consumption and carbon dioxide production to estimate energy expenditure under controlled conditions. It is commonly treated as the reference method when an accurate individual resting measurement is clinically or professionally important.

Even a measured resting rate does not directly tell you total daily expenditure. You still need to account for food digestion, spontaneous movement, work and exercise. But it removes one layer of prediction from the process.

For ordinary weight management, indirect calorimetry is not necessary for everyone. A well-chosen equation plus careful tracking is often sufficient for planning. For complex cases—especially where predictive methods repeatedly fail or there are clinical concerns—a qualified dietitian or clinician can decide whether measurement is useful.

Mifflin-St Jeor vs Katch-McArdle comparison

Worked comparison: how body-fat error changes Katch-McArdle

Suppose someone weighs 80 kg. If they estimate 20% body fat, lean mass is 64 kg. Katch-McArdle gives:

370 + (21.6 × 64) = 1,752 kcal/day.

Now imagine the true body-fat level is closer to 27%. Lean mass would be 58.4 kg:

370 + (21.6 × 58.4) = 1,631 kcal/day.

A seven-percentage-point body-fat error changes the estimate by roughly 121 calories per day. That may not sound enormous, but it illustrates why a body-composition equation is only as good as its input.

What if my smart scale gives a body-fat percentage?

Bioelectrical impedance scales can be useful for monitoring trends when conditions are consistent, but the displayed body-fat percentage should not be treated as laboratory truth. Hydration, food intake, recent exercise and device algorithms can influence the result. If you use that value in Katch-McArdle, keep the uncertainty in mind.

A practical strategy is to calculate both formulas. If Katch gives a very different result from Mifflin because your scale reports an unexpectedly low or high body-fat percentage, do not assume Katch is automatically the sophisticated answer. Your later weight trend can tell you which calorie range behaves more realistically.

What about very muscular people?

A muscular person may find a lean-mass-based equation appealing because scale weight alone cannot distinguish muscle from fat. That is reasonable, but still does not guarantee accuracy. If you have a high-quality body-composition assessment, Katch-McArdle can be a useful second estimate. If you only have a visual guess, it may be safer to use Mifflin as the baseline and adjust from observed maintenance intake.

What about people with obesity?

Mifflin-St Jeor has been studied in both non-obese and obese adults and is commonly used in general practice, but individual prediction errors remain possible. For someone whose calorie needs are clinically important, professional assessment is preferable to repeatedly switching online formulas.

Katch-McArdle is not automatically better for higher body-fat levels because it requires a dependable lean-mass estimate. Some body-composition methods become less precise at individual level, and the equation itself still remains predictive.

What about older adults?

Age is explicitly included in Mifflin-St Jeor. Katch-McArdle does not use chronological age directly; it relies on lean mass to capture some variation. Older adults can differ in muscle mass, health status and metabolic characteristics, so neither equation should be treated as guaranteed. If unintentional weight loss, frailty, illness or nutritional risk is present, a general calorie calculator is not a substitute for clinical advice.

How the formula affects TDEE

A difference in resting estimates becomes larger after an activity factor is applied. Suppose Mifflin gives 1,600 calories and Katch gives 1,750. At an activity multiplier of 1.55:

• Mifflin-based TDEE: 1,600 × 1.55 = 2,480 kcal
• Katch-based TDEE: 1,750 × 1.55 = 2,712.5 kcal

The difference is now more than 230 calories per day. That is enough to affect the expected rate of weight change, particularly over several weeks.

This is also why it is unhelpful to obsess over the “perfect” resting equation while casually choosing an activity multiplier. Both steps can introduce error. Read our guide to TDEE activity levels if choosing sedentary, light or moderate activity is your main uncertainty.

A practical decision tree

Use Mifflin-St Jeor first if:

• You do not know your body-fat percentage.
• Your body-fat estimate comes only from a visual guess.
• You want a simple general-population starting estimate.
• You plan to calibrate the result with real-world data anyway.

Consider Katch-McArdle as an alternative if:

• You have a reasonably reliable lean-mass or body-fat assessment.
• You are substantially more muscular than average and want a comparison.
• You understand that the result remains an estimate.
• You are willing to test it against your actual maintenance intake.

Seek professional measurement or advice if:

• Nutrition is part of treatment for a medical condition.
• Your predicted needs repeatedly make no sense despite careful tracking.
• You have unexplained weight change.
• You are pregnant, breastfeeding, under 18, frail, or have specialist nutritional needs.
• You have a current or previous eating disorder and calorie tracking may be inappropriate.

How to validate either formula in real life

The most useful calorie estimate is the one that becomes more accurate through feedback. After calculating TDEE, choose a consistent intake and monitor average body weight for several weeks. Use similar weigh-in conditions and compare weekly averages rather than single readings.

If intake and weight are stable, your average intake is providing practical evidence about maintenance. If weight consistently decreases, expenditure is probably above intake. If it increases, intake is probably above expenditure. The exact conversion between calorie imbalance and scale change is not perfectly fixed because water, glycogen and body composition also change, but the direction over time is highly useful.

Make modest adjustments rather than replacing the whole equation every few days. The point is to calibrate the estimate, not to win an argument about formulas.

Why two calculators can disagree

Even when both calculators claim to use Mifflin-St Jeor, differences can arise from rounding, activity multipliers, how the site defines sex, whether exercise is added separately, whether a thermic-effect allowance is built in and whether the output is labelled BMR, RMR or TDEE. Always compare the underlying assumptions, not just the final number.

Which formula should you use for fat loss?

Use the formula that gives the most defensible maintenance starting point, then create a deliberate deficit from that maintenance estimate. Mifflin is often the easier starting point because it does not require body-fat data. If Katch is based on a strong body-composition measurement and produces a plausible result, it can be used instead or as a comparison.

Do not choose the lower formula simply because you want faster weight loss. The equation is supposed to estimate expenditure, not decide your diet aggressiveness.

Which formula should you use for muscle gain?

Again, estimate maintenance first. Muscular lifters may find Katch-McArdle informative, but the real-world rate of gain matters more than theoretical precision. If body weight is not rising despite a consistent intake, the practical solution is usually a measured calorie adjustment, not repeated formula switching.

Common mistakes

1. Treating body-fat percentage as exact

An input shown to one decimal place can still be an estimate with meaningful uncertainty.

2. Calling Mifflin “wrong” because it does not use body fat

Simple models can outperform more complex ones when the extra input is noisy.

3. Choosing whichever answer matches what you want to eat

That introduces confirmation bias. Let later data decide which range is realistic.

4. Forgetting the activity multiplier

The difference between formulas may be smaller than the error caused by selecting the wrong activity category.

5. Expecting calculators to detect metabolic adaptation

Predictive equations use population relationships. They do not directly measure an individual’s current adaptive response to prolonged dieting, illness or training.

Frequently asked questions

Is Mifflin-St Jeor more accurate than Katch-McArdle?

There is no universal winner for every individual. Mifflin has strong practical evidence in general adult populations and does not require body-fat data. Katch may be useful when lean mass is reliably known, but body-fat error can reduce its advantage.

Is Katch-McArdle better for bodybuilders?

It can be a useful comparison because it uses lean mass, but research in athletes shows predictive equations can still miss individual RMR. Use the result as a starting estimate and validate it.

What body-fat method should I use for Katch-McArdle?

Use the best-quality assessment reasonably available to you and understand its limitations. A professionally performed method is generally more useful than a casual visual guess. Consistent conditions matter for repeat measurements.

Can I average Mifflin and Katch?

You can use the midpoint as a pragmatic starting estimate if both inputs are credible and the values are reasonably close. There is no physiological rule saying the average is automatically more accurate, so still test it.

Why does Katch give me fewer calories?

If your estimated lean mass is relatively low for your total weight, the formula may produce a lower result. Check whether your body-fat input is credible before interpreting the difference.

Why does Katch give me more calories?

A high estimated lean mass can raise the result. This is common in muscular users, but an underestimated body-fat percentage can also inflate the lean-mass input.

Can I calculate Katch-McArdle without body-fat percentage?

Only if you already know lean body mass from another method. Otherwise, lean mass must be estimated somehow.

Which equation does a calorie calculator use?

It varies by calculator. Check the methodology. The equation for resting needs and the activity method should both be stated if you want to understand the output.

Should I recalculate after losing weight?

Yes. A material change in body weight changes formula inputs and often changes total expenditure. Your activity may also change during a long diet.

Is a 100-calorie difference important?

It can matter over time, but normal tracking error and daily expenditure variation can also be larger than people realise. Do not chase tiny differences while ignoring consistency.

Bottom line

For most adults without a reliable body-composition measurement, Mifflin-St Jeor is a sensible starting formula. It uses easily measured inputs and has performed comparatively well in research on common RMR prediction equations. Katch-McArdle is valuable when you have credible lean-mass data or unusually high muscularity, but its apparent personalisation does not eliminate error.

The strongest approach is not to search indefinitely for one perfect formula. Calculate a reasonable starting range, use The Dryden’s TDEE Calculator to translate resting needs into an overall estimate, keep your activity assumptions realistic, and refine the result from real-world trends.

Sources and further reading

• Frankenfield et al.: comparison of predictive equations for resting metabolic rate
• Systematic review of resting metabolic rate prediction equations in athletes