We offer a heuristic approach for using psychometric indicators to resolve questions in the classification of schizophrenia and elucidation of its clinical and genetic boundaries. A combination of signs derived from the Minnesota Multiphasic Personality Inventory (MMPI) was used to provide evidence for the accuracy of parental phenotypic assessments and the determination of risk for schizophrenia in children in the New York High-Risk Study. The MMPI indicators were useful in discriminating schizophrenia defined by the Research Diagnostic Criteria (RDC) from psychotic and nonpsychotic affective illness and normality, with moderately high to high predictive power, specificity, and sensitivity. Kappa calculations showed a high rate of chance-corrected diagnostic agreement for schizophrenia between the RDC and the MMPI. The data provide tentative support for the allocation of schizoaffective cases to one of two syndromic clusters related to either schizophrenia or affective illness. An exploratory attempt was made to demarcate schizophrenia as a discrete disorder separated by qualitative psychometric boundaries. The imprecision of the current psychiatric nosology may lead to difficulties in resolving distinctions between the functional psychoses, and we propose that use of both psychometric data and fixed diagnostic criteria can lead to a more valid definition of schizophrenia.