Nowadays, medical diagnosis reasoning is a very important application area of the computer-based systems. Case-Based Reasoning (CBR) has become a successful technique for developing medical diagnosis systems. This system presents a CBR methodology and the technical aspects of implementing a medical diagnosis system. CBR is a recent approach to problem-solving and learning that has got a lot of attention over the last few years. In the case-based reasoning system, old cases are retrieved to solve user input problems or new cases. To be a complete CBR system, case adaptation is used to revise and retain the new case for future use when no match case is found in the casebase. This system is implemented as a case-based reasoning system for Kidney and Urinary Tract Diseases. In this system, the K-Nearest Neighbor classifier (KNN) is used for case retrieval. If the result of the input case is not satisfied, the adaptation process will be done. Decision Tree algorithm is used in case adaptation.