The testing result of the medical knowledge-based system for diagnosis from symptoms and signs is found that the diagnosis of the system more than 97% accurately at the 0.01 level of significance, when it is compared with diagnosis of a physician. Although the accuracy of knowledge for diagnosis is an important variable to indicate the accuracy of system, but data is imported from patients that have some effects. These effects are occurred from the confusion and hesitation of patients. So the medical knowledge-based system requires a method for resolving the uncertain data such as Fuzzy inference or certainty factor. For the experimental results, we compare diagnostic results between system and a physician in each case. So if we use physicians, who are more than one person, for each case, and we use a group of medical expert humans to diagnose the patient then the medical knowledge-based system is completely. Additionally it should have diagnosis following, which help the system that is believable. However a physician may be missing diagnosis in sometimes because he is absolutely in body, emotion, times, or another factors. Finally we can say that the medical knowledge-based system for diagnosis from symptoms and signs is a tool for help to create medical knowledge-based system.