The prevalence and demographic and clinical correlates of lifetime substance use disorders were examined in a cohort of 325 recently hospitalized psychiatric patients (53% schizophrenia or schizoaffective disorder). Alcohol use was the most common type of substance use disorder, followed by cannabis and cocaine use. Univariate analyses indicated that gender (male), age (younger), education (less), history of time in jail, conduct disorder symptoms, and antisocial personality disorder symptoms were predictive of substance use disorders. Lifetime cannabis use disorder was uniquely predicted by marital status (never married) and fewer psychiatric hospitalizations during the previous 6 months. Optimal classification tree analysis, an exploratory, nonlinear method of identifying patient subgroups, was successful in predicting 74 percent to 86 percent of the alcohol, cannabis, and cocaine use disorders. The implications of this method for identifying specific patient subgroups and service needs are discussed.