Prostatic carcinoma is the fifth most common cancer in the world and the second most common in men. It is quite important to early detect and diagnose prostate cancer to reduce the mortality. With the increasing of the diagnosis and treatment tasks of prostate cancer and the development of medical techniques, more and more clinical and lab examinations, biopsy and medical imaging techniques are included in the diagnosis of prostate cancer. Although these examination results are supplement to each other, there are contradictions among them at the same time. Artificial neural networks (ANNs) which can perform multifactorial analysis based on computational methodologies have been widely used in the prognosis of prostate cancer. The current application of ANNs is reviewed.