Physicians take both diagnosis and prognosis into account when allocating treatment. However, by "prognosis" physicians usually imply a somewhat vague impression concerning large groups of patients. One possible task for decision support studies is to design and construct systems that accurately predict individual patient prognoses. The authors constructed and tested such systems in three areas of medicine (inflammatory bowel disease, upper gastrointestinal tract hemorrhage, and acute chest pain). In each area, the individual patient's symptoms were compared with a computer-held database of information via a Bayesian analysis, prior and conditional probabilities being derived from large-scale real-life surveys. Prospective trials designed to test these predictive systems by reference to test series comprising over 4,000 patients indicate that a firm prognostic prediction can generally be made; where made, the accuracy of prediction is over 90%. Ways in which this type of prediction may be of clinical value are discussed.