Prostate cancer is one of the well-known explanations of death for males each year. In the most severe cases, the prostate cancer spreads quickly, bursts through the capsule, infects surrounding organs, or separates and enters the bloodstream, where it is subsequently carried to other areas of the body where it continues to develop and finally fails organs. This research suggested using a knowledgeable system to identify prostate cancer. The fuzzy expert system was created to diagnose men of various racial and age ranges for prostate cancer at an early stage. The smart system is situated on the Fuzzy inference system, which predicts the existence or absenteeism of prostate cancer utilizing the Matlab program and a graphical user interface. Employing a reference range and a few key characteristics, the systems are designed to identify prostate cancer at any stage, from early to malignant. Vital indicators including age, ethnicity, biopsy results, PSA levels, and so on were used as inputs. Three sections were intended for the output: good, negative, and suspicious. The research processed the input data using knowledge-based rules and produced a helpful diagnostic as an output.