Recent cluster analytic research with alcoholic inpatients has demonstrated the existence of several Millon Clinical Multiaxial Inventory (MCMI) clusters that appear to be consistent across different subject samples. The validity of these data would be strengthened by a statistical demonstration of the similarity of attained clusters across studies--a demonstration of concordance of subject classification across different clustering techniques on the same data set- and the inclusion of external, independent measures against which to evaluate the predictive validity of the cluster typology. We found a high level of concordance in subject classification across different clustering methods on the same data set and a high level of agreement with cluster typologies attained in previous studies. Subsequent multivariate analyses employing independent scales measuring various aspects of alcohol use confirmed differences among cluster members on perceived benefits of alcohol use and deleterious effects of alcohol use. The prominent differences in alcohol use along with a rationale for their development are discussed.