Fuzzy logic is a computational paradigm that provides a mathematical tool for dealing with the uncertainty and the imprecision typical of human reasoning. A prime characteristic of fuzzy logic is its capability of expressing knowledge in a linguistic way, allowing a system to be described by simple, human-friendly rules. The fuzzy set framework has been utilized in several different approaches to modeling the diagnostic process. In this paper Diabetes related diseases and their symptoms are taken. The physician’s medical knowledge is represented as a fuzzy relation between symptoms and diseases. Thus, given the fuzzy set A of the symptoms observed in the patient and the fuzzy relation R representing the medical knowledge that relates the symptoms in set S to the diseases in set D, then the fuzzy set B of the possible diseases of the patient can be inferred by means of the compositional rule of inference. Fuzzy membership values for representing different symptoms are framed and they are used for forming the relations.