Knowledge of body condition is important in predicting health and performance of large mammal populations. Therefore, we assessed body condition in black bears (Ursus americanus) in Rocky Mountain National Park (RMNP), Colorado, using body mass (BM), percent body fat (BF) and a body condition index (BCI) to: (1) develop a model predictive of BM for bears in RMNP using morphometric measures, (2) compare three models predictive of BM to provide further information on the influence of elevation and more complex models on model accuracy, and (3) assess the relationship between BF and BCI to determine if BF could be estimated from BCI. Our best BM model included only girth (r²  =  0.923) and indicated that mass-morphology relationships were more consistent within specified elevation zones; complexity of models had little influence on model efficiency. We also observed a strong relationship between BF and BCI (r²  =  0.962) indicating that BCI scores can be accurately converted to estimates of BF. This predictive equation should prove useful to black bear managers in situations where BF cannot be estimated using more direct methods.