Advances in risk assessment have improved the ability to identify psychiatric patients at high risk for violence. Identifying these patients is necessary for developing treatment to address their needs. However, if violence is caused by risk factors that vary across patients, relatively homogeneous subgroups of high-risk patients must be identified and studied to develop effective risk management programs for each. This study was designed to identify and describe valid subtypes of patients reliably identified as at high risk by the multiple Iterative Classification Tree (ICT) risk assessment approach. After existing typologies of violent individuals were integrated to develop hypothesized subtypes of high-risk patients, data on 165 patients identified as at high risk by the multiple ICT were used to determine whether clinically meaningful subtypes could be identified and externally validated. Three groups (alpha, beta, and delta) largely consistent with the hypothesized subtypes and their correlates were identified. The implications of these findings for research and treatment development efforts are discussed.