Effective management of knowledge is essential for a CPA firm to remain competitive. Use of computational models of judgment processes and outcomes causes knowledge to be available for use and analysis. We present a comprehensive and integrated computational model of the difficult and knowledge‐intensive judgments needed for successful audit planning. The model concludes on a client's going‐concern status, applicable levels of inherent, control, and planned detection risk, and appropriate levels of statement‐ and account‐level materiality. Most importantly, the model validly identifies the cause of significant fluctuations given causal hypotheses. The context is the sales and collection cycle of a manufacturing client. The model consistently replicates causal hypothesis judgments generated by the modeled auditor who exhibits considerable judgment expertise, i.e., his judgments typically coincide with actual causes. Concerning judgment expertise, the model reveals numerous linkages among judgments, subtle interdependencies in cue importance across judgments, and new findings concerning cue diagnosticity.

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