In the wake of population aging, prostate cancer has become one of the most important diseases in elderly men. The low specificity in only image-based diagnosis may lead to unnecessary biopsies. Therefore, clinicians need to consider other variables to make diagnosis, such as age, PSA, and prostate volume. In this study we developed a novel 3D CNN model which combined clinical parameters and MR images for differentiating benign and malignant prostate lesions. The area under the receiver operating characteristics (ROC) of our proposed model (0.84) is significantly higher than that of traditional prediction model (0.71, P < 0.001).