Prostate cancer is the second cancer with the highest incidence worldwide in men and is characterized by the excessive proliferation of cells in the prostate gland. Due to this incidence, this pathology's correct and timely identification has become important. Currently, the accurate diagnosis of prostate cancer is made through biopsy, however, performing a biopsy on each suspected person entails discomfort and can even trigger health problems in patients. For this reason, other methods that are based on clinical variables are seeking to be implemented, which could avoid unnecessary biopsies. In this thesis work, the main objective was to develop an Artificial intelligence-based algorithm that allows the correct prediction of prostatic cancer using MATLAB.