Despite the existence of counseling dropout research, there are limited predictive data for counseling in training clinics. Potential predictor variables were investigated in this archival study of 380 client files in a university counseling training clinic. Multinomial logistic regression, predictive discriminant analysis, and classification and regression trees converged on the use of a 4-predictor model (client age, income, perceived difficulty, and functional impairment) for classifying counseling dropouts. Implications for research and practice are discussed.