The importance of single symptoms in the diagnostic process has not been adequately studied, mainly because of the complexity of the information involved. The aim of the present study is to investigate the interconnection between psychopathological assessment and diagnostic classification, with the aid of a nonparametric, inductive pattern recognition method. Using the concept of inductive logic and a theory of inductive knowledge acquisition, a model has been developed to describe psychopathological assessment and diagnostic classification. Based on a comprehensive psychopathological assessment in 837 patients with 14 different diagnoses, classification values were calculated for specific symptoms in different diagnostic groups. Furthermore, nonparametric statistical procedures have advantages over discriminant analytic approaches: more information is utilized in differentiating the groups and differentiations can be made between more groups, whereby the rate of correctly classified cases is comparable with discriminant analytic approaches. The pattern recognition method appears to illustrate the multidimensional, medical decision-making in a comprehensible way.