Purpose: In our study, we sought to improve the accuracy of predicting the risk of hospitalization and to identify older, inner-city patients who could be targeted for preventive interventions. Design and Methods: Participants (56% were African American) in a randomized trial were from a primary care practice and included 1,041 patients living in the inner city who were either [greater than or equal to] 75 years of age or were [greater than or equal to] 50 years of age with severe disease. As a secondary analysis, we assessed patient characteristics at baseline involving five domains of health, including utilization and satisfaction. We followed participants for 12 months and recorded the occurrence of nonelective hospitalization within the study period. We developed a multivariate model using logistic regression to predict this outcome. Results: The following patient characteristics independently predicted an increased risk for nonelective hospitalization: having the diagnosis of congestive heart failure, diabetes mellitus, or anemia; and having more medications prescribed, having a lower body mass index, and having more emergency department visits during the previous year. Better physical functioning reduced the risk of hospitalization. Implications: Moderate accuracy of a prediction model (0.73) was observed. In addition to focusing on patients with chronic disease, helping them maintain physical functioning may help reduce nonelective hospitalization.