The objective of this study was to identify on admission the most discriminating fall predictors for patients to an inpatient rehabilitation unit. Medical information from 34 patients who fell over a consecutive 7-month period and 102 controls (1:3 ratio) matched for diagnosis, age, and gender was analyzed to identify a set of best predictors. Admission mobility and problem solving FIM™ scores accounted for 17% of variance in whether a fall occurred during the admission. After statistically deriving optimal cutoff thresholds for decision making, high fall risk was retroactively assigned to patients. Logistic regression revealed increased odds of having fallen by 5.1 times for poorer mobility and 2.4 times for poorer problem solving. The practical benefits of the evidence-based risk assessment were discussed.