This paper focuses on visual data mining methods for prostate cancers. The most common cancer among US men is prostate cancer. It is estimated that in the year 2002, 189,000 US men were diagnosed with prostate cancer, of which 30,200 died. Even with these alarming numbers, there is still no universally agreed-upon strategic plan for the diagnosis and management of prostate cancer. One of the contributing factors to why there is no universal treatment of prostate cancer is because treatment requires individualized care. Depending on the details of the prostate cancer, such as severity, locality, recurrence, patient age, patient life expectancy, etc..., a particular treatment method or cocktail of management care is prescribed. In this paper, we explore these variables using the CrystalVision data mining tool.