PURPOSE The purpose of this project was to predict VO2 at the ventilatory threshold (VO2vt) based on sustainable fitness data collected from self-report questionnaires. Equations to predict VO2vt were developed based on descriptive data and reported intensity of sustained exercise. METHODS Male and female subjects of varying age and fitness (N=63) each completed a Sustainable Fitness Questionnaire, compiled at the University of Montana, to estimate average exercise energy expenditures. A graded treadmill test with collection of metabolic gases was used to determine VO2vt. During the treadmill tests subjects walked at a constant self-selected speed and the treadmill grade was increased one percent each minute. HR and RPE were collected each minute. Following testing, the questionnaires were coded using the Compendium of Physical Activities. Maximal sustained VO2 during exercise (VO2sustained) was estimated based on these results. Stepwise multiple regression models were used to develop prediction equations for VO2vt. Cross validation was completed using the PRESS cross validation method. RESULTS When the group was analyzed as a whole, using VO2vt as the outcome variable, gender and VO2sustained were significant at the p < 0.01 level when added into the stepwise multiple regression model (R2=0.493). When multiple regression analysis was completed by gender the results were improved for the males (R2=0.626), but were not improved for the females (R2=0.495). Separation by fitness level improved the predictive ability of the models. For the lower fit group both BMI and gender were added to the model (R2=0.674). For the higher fit group BMI and maximal sustained VO2 of reported activity levels were added to the model (R2=0.734). CONCLUSIONS These data show that gender and VO2sustained are significant predictors of VO2vt when analyzing diverse populations. Separation by sex, fitness level and intensity of chronic activity also improved the predictive ability of the models.