The selection of dryers is an art in which knowledge, experience and science all play important roles. Historically, dryer selection has been made by experts on the basis of their extensive knowledge. However, in recent years, computer-based techniques have been developed, which have the potential of at least partially deskilling this process. Of the various possibilities, fuzzy expert systems, in which the selection qualifiers are represented as linguistic rather than numerical variables, are the most promising. This paper describes the development of a fuzzy system for the selection of batch dryers for food products. It featured a novel modular approach in which independent selection goals for dryer type, atmospheric, vacuum or freeze operation, and single or multiple units were adopted. This made the system particularly flexible and amenable to adaptation. The program starts from a ‘ drying process checklist“ in which the principal process variables are specified, and provides a ranked list of feasible alternative dryers. The algorithm was extensively tested and provided quite plausible results. Four representative case studies are presented and discussed.