This article illustrates how a cluster analysis can be conducted, validated, and interpreted. Data normed for a behavioral assessment instrument with 14 scales on a nationally representative sample of U.S. school children were utilized. The discussion explores the similarity index, cluster method, cluster typology, cluster validity, cluster structure, and prediction of cluster membership. The Behavior Assessment System for Children (BASC) form that assessed 6- to 11-year-old students with the Teacher Rating Form (TRS-C) was used with a sample of 1,228 elementary school children. The clustering method involved a two-step procedure: a Ward hierarchical analysis followed by an iterative cluster partitioning via a K-means analysis. As illustrated, the following steps are suggested for cluster analysis: (1) select the study units (children); (2) choose the system of response variables; (3) decide how to measure the response variables; (4) select the similarity index; (5) select the cluster method; (6) determine the initial cluster typology; (7) provide some evidence of cluster validity; (8) interpret final cluster typology; (9) describe final cluster structure; and (10) develop a classification rule for new units. (Contains 2 figures, 9 tables, and 48 references.) (SLD)