Management of patients diagnosed with localized prostate cancer is complicated by the diverse natural history of the disease and variable response to treatment. Prognostic criteria currently in use cannot fully predict tumor behavior and thus limit the ability to recommend treatment regimens with the assurance that they are the best course of action for each individual patient. The search for better prognostic markers is now focussed on the molecular mechanisms which underlay tumor behavior, such as altered cell cycle progression, apoptosis, neuroendocrine differentiation, and angiogenesis. As the number of potential molecular markers increases, it is becoming evident that no single marker will provide the prognostic information necessary to make a significant improvement in patient care. In addition, it seems likely that traditional methods of assessing the prognostic value of this multitude of new markers will prove inadequate. In this review, we briefly examine the current state of prognostication in localized prostate cancer and some of the promising new molecular markers. Next, we examine how new technologies may allow the multiplex analysis of vast numbers of markers and how computational methods such as artificial neural networks will provide meaningful interpretation of the data. In the near future, such an integrated approach may provide a comprehensive prognostic tool for localized prostate cancer.