Background: Limited information is available about the characteristics of consumers accessing community-based residential mental health rehabilitation units. This study used exploratory statistical analysis techniques to identify meaningful subgroups of consumers admitted to these services. Objectives: Guiding practice and policy in relation to this low-volume, high-cost component of the mental health services array by achieving a better understanding of ‘who’ is admitted. Methods: Hierarchical cluster analysis (Wards method) to identify the optimal number of clusters, followed by K-means clustering. Clusters were then comparison of clusters based on demographic, diagnostic, clinical assessment and treatment-related variables. Findings: A three-cluster solution emerged. Cluster 1 (15%) was characterised by higher levels of substance use comorbidity. Cluster 2 (39%) was characterised by higher levels of disability and symptoms; and Cluster 3 (46%) was distinguished by lower levels of general psychiatric symptoms. Important differences were present in the assessed stage of recovery using the Scoring the Stages of Recovery Instrument-30 between the clusters. Conclusions: The cluster solution suggests the relevance of adapting the approach to rehabilitation. Recommendations include ensuring early availability of interventions to address comorbidities and pacing rehabilitation expectations to consumers’ stage of recovery.