Urologists store a large amount of data about the patients they treat who suffer from prostate cancer. This data is essential for tracking the tumor and knowing the patient's current status at all times, as well as determining the best treatment to apply. This article describes a web application that allows managing medical records of patients with diseases related to prostate cancer and offers a set of prediction functions. Specifically, it allows predicting the behavior and evolution of prostate cancer, calculating the probability of having prostate cancer, and whether it will be more or less aggressive, and obtaining a tree diagram with the different treatments that may be needed, marking the most appropriate one in each case and recommending possible actions to follow for surveillance. To do this, statistical models of linear regression and AI algorithms are applied to clinical, analytical, radiological parameters, etc., reflected in the medical records of a database of patient medical records.