The purpose of this study was to produce the regression equation from non-exercise of healthy young adults and to develop a maximal oxygen consumption () regression model. This model was based on heart rate non-exercise predictor variables (rest heart rate, maximal heart rate/rest heart rate), as an extra addition to the general regression which can reflect an individual's inherent or acquired cardiorespiratory fitness. The subjects were 101 healthy young adults aged 19 to 35 years. Exercise testing was measured by using a Balke protocol for treadmill and indirect calorimetry. The prediction equation was analyzed by using stepwise multiple regression procedures. The mean of was (meanSD). The greatest variable correlated to was %fat. The predictor variable used in the non-exercise included %fat, gender, habitual physical activity and . The non-exercise estimation was as follows: ()=55.58-.41(%fat)+.59(physical activity rating)-2.69()-5.36 (male=0, female=1); (R=.85, SEE=3.64, R2=.72: including heart rate variable); ()=48.47-.41(%fat)+.45(physical activity rating)-5.12 (male=0, female=1); (R=.84, SEE=3.74, R2=.70: with the exception of heart rate variable). As an added heart rate variable, there was only a 2% coefficient of determination improved. Therefore, these results demonstrated that heart rate variable correlation with a non-exercise regression model was very low. In conclusion, for healthy young korean adults, those variables that can affect non-exercise estimation turned out to be only % fat, gender, and physical activity. We suggest that further research of predictor variables for non-exercise is necessary for different patient groups who cannot perform maximal exercise or submaximal exercise.