A stepwise search procedure is proposed for the selection of binary variables for discriminant analysis and differential diagnosis. The discriminant procedure described exploits the dependencies among the variables. Bayes estimates of the probability of correct diagnosis based on exchangeable priors are derived. The estimation procedure provides a natural stopping rule for the inclusion of variables. An application to tumour diagnosis is considered and a simple diagnostic key constructed.