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Estimated Lung Capacity Calculator

Estimate your predicted vital lung capacity based on age, height, and sex.

Result

Predicted Vital Capacity
4.72 L

Uses a standard population-regression formula for predicted vital lung capacity based on age, height, and sex. Actual lung capacity varies with fitness level, smoking history, altitude, and respiratory health - a spirometry test performed by a healthcare provider is the accurate way to measure your actual lung function.

About the Lung Capacity

The Estimated Lung Capacity Calculator predicts your vital capacity, the maximum volume of air you can exhale after a full inhale, using a population-based regression formula built from age, height, and sex. It lets you see where your lungs are expected to fall relative to population averages without needing access to a spirometer. Runners, swimmers, and anyone curious about respiratory capacity can use it as a quick reference point.

How It Works

You enter your age, height in inches, and sex. The calculator converts height to centimeters and applies one of two linear regression equations, one calibrated for men and one for women, each combining a height coefficient, an age coefficient, and a constant. The output is expressed in liters and floored at zero so extreme inputs can't produce a negative predicted capacity.

Height is converted from inches to centimeters (height_cm = height_in x 2.54). For men: Vital Capacity (L) = 0.052 x height_cm - 0.022 x age - 3.6. For women: Vital Capacity (L) = 0.041 x height_cm - 0.018 x age - 2.69. The result is floored at 0 liters.

Examples

Adult male, average height

A 30-year-old man who is 68 inches tall (172.72 cm) gets a predicted vital capacity of 0.052 x 172.72 - 0.022 x 30 - 3.6, which works out to about 4.72 liters.

Adult female, comparing two ages

A 65-inch-tall woman (165.1 cm) predicts to about 3.63 liters at age 25, but roughly 3.09 liters at age 55, illustrating the formula's built-in age-related decline for the same height.

Advantages

  • Requires no special equipment, just age, height, and sex, to produce an instant predicted vital capacity figure.
  • Uses separate regression equations for men and women, reflecting average differences in chest cavity size and lung tissue between sexes.
  • Provides a useful population-level reference point to compare against an actual spirometry reading if one is available.

Common Mistakes

  • Assuming the predicted number is a diagnostic measurement rather than a population-average estimate that ignores individual respiratory health.
  • Entering height in centimeters into a field meant for inches, which skews the result since the calculator performs its own inch-to-centimeter conversion internally.
  • Expecting the result to reflect fitness or training gains, when the formula only varies with age, height, and sex and has no input for cardiovascular conditioning.

Edge Cases to Watch For

  • For unusually young ages or short heights entered outside realistic adult ranges, the formula can mathematically produce a negative value, which the calculator floors at 0 liters rather than displaying an implausible negative number.
  • The formula treats age as a straight-line decline in lung capacity, a simplification since real respiratory decline is not perfectly linear across the entire adult lifespan.
  • Smoking history, altitude, asthma, and fitness level are not inputs to this formula, so two people with identical age, height, and sex but very different respiratory health receive the same predicted value.

Common Use Cases

  • Endurance athletes wanting a rough benchmark for expected lung capacity based on their basic stats.
  • Students or health enthusiasts learning how predicted vital capacity regression formulas work.
  • Anyone comparing an actual spirometry test result against a population-predicted baseline for context.
Written & fact-checked by the Calculateus TeamLast updated August 5, 2026How we verify our formulas

Frequently asked questions

Why does height factor so heavily into predicted lung capacity?

Taller people generally have proportionally larger chest cavities and lungs, so height serves as a useful proxy for expected lung size in population-level prediction formulas, alongside age (since lung tissue elasticity and capacity gradually decline with age) and biological sex (reflecting average differences in chest cavity size and lung tissue).

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Conclusion

This calculator distills a standard predicted vital capacity regression into a simple three-input tool. It works best as a general reference point rather than a substitute for an actual pulmonary function test.

References