An important goal of clinical assessment is to balance cost-effectiveness, administration demands, and accuracy (G. Young, J. O'Brien, E. Gutterman, & P. Cohen, 1987). The incorporation of Bayesian logic into diagnostic interviewing may assist with this goal, but in previous examinations, such methods have been prohibitively complex. In this study, analysis of a simplified Bayesian system showed overall classification error rates as good or better than traditional structured interviewing, and reduction in error was positively related to the psychometric properties of the predictor used in the actuarial functions. A dynamic system using simplified Bayesian logic appears to function well in the context of a structured interview and requires comparatively less data than previously tested Bayesian approaches. This type of system appears suitable for further research with clinical populations to determine its performance in applied settings.