The problem of predictive diagnosis based on laboratory data is approached from a mathematical standpoint. A descriptive system is introduced which examines the current information about a clinical problem and identifies best predictors of the problem. Algorithms are described for the assessment of current diagnostic ability, the evaluation of new laboratory tests, and the identification of patients to study for the development of new procedures. The laboratory approach to the predictive diagnosis of iron deficiency is chosen as an example of the system.