Abstract: A computer-implementable method of selecting which engine of a plurality of inference engines to use to predict the categories into which individuals fall, such as buyer/non-buyer, and produce forecast reports based on the predictions is disclosed. Training (known) sample data that categorizes individuals based on the individual's profile is sequentially applied to multiple inference engines to determine which engine is best based on a desired objective. Then, a classifier associated with the selected engine is used to analyze unknown sample data, create category predictions and produce forecast reports based on the predictions.