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ABSTRACT Context: Bone stress injuries (BSI) have been recognized as one of the most common and potentially serious overuse injuries in military training and result in negative impacts on service member health and force readiness. Several studies have purported to develop a prediction model that could successfully identify individuals in military training at high risk for BSI, but none are currently acceptable for implementation for one or more reasons. Objective: To develop an accurate, parsimonious prediction model for BSI risk in a military training population using easily obtained and interpreted predictor variables. Design: Prospective cohort study. Setting: US Military Academy at XXX. Participants: 3,227 (749 females, 23.2%) incoming cadets. Main Outcome Measures: A multivariable prediction model for BSI risk during the first year of cadet training was created using potential predictor variables related to demographics, anthropometrics, exercise and injury histories, and lower extremity movement quality. A scree plot of change in model log likelihood value was used to guide selection of variables in the final model. Performance of this model was assessed for calibration (i.e. goodness-of-fit) and discrimination (i.e. prognostic accuracy). Minimum acceptable criteria for each were determined a priori . Results: A total of 63 BSI occurred in the study period. The final model consisted of sex and running frequency prior to entry. Performance of this model was sufficient on some measures analyses revealed that an expanded model consisting of all predictor variables also did not reach minimum acceptable calibration or discrimination criteria. Conclusions: Despite use of a large dataset and several predictor variables with well-established associations with BSI risk, we were unable to develop a prediction model for BSI risk with adequate prognostic accuracy properties using a set of easily obtained predictor variables.