Background: Given the significant behavioral heterogeneity characterizing children with neurodevelopmental disorders and disabilities (NDD/D), the current study examined whether cluster analysis could classify a diverse sample into more homogeneous subgroups. Aims: We first utilized cluster analysis to identify subgroups of children demonstrating similar behavior profiles. Second, we investigated the distribution of children's primary diagnoses represented within each cluster. Finally, we compared the clinical utility of clusters versus diagnoses for indices of child and family health. Methods: Caregivers provided data for 222 children with NDD/D (M = 8.22 years), completing measures of child behavior and child and family health. Results: A 4-cluster solution was revealed: Social Difficulties, Cross-domain Difficulties, Hyperactive-inattentive, and Low difficulties, and a range of conditions was found within each. For all indices of child and family health, clusters explained greater variance than did diagnoses. Conclusions: The current study provides new insight into the heterogeneous nature of behavior among children with NDD/D. Considering a child's unique constellation of strengths and difficulties may serve as a clinically meaningful supplement to diagnosis that more fully elucidates functional profile.