The success of focal salvage treatments for recurrent prostate cancer after radiation therapy relies on accurate detection and delineation of the treating target. A logistic regression model based on multiparametric magnetic resonance imaging was used to Purpose: Focal salvage treatments of recurrent prostate cancer (PCa) after radiation therapy require accurate delineation of the target volume. Magnetic resonance imaging (MRI) is used for this purpose; however, radiation therapyeinduced changes complicate image interpretation, and guidelines are lacking on the assessment and delineation of recurrent PCa. A tumor probability (TP) model was trained and independently tested using multiparametric magnetic resonance imaging (mp-MRI) of patients with radio-recurrent PCa. The resulting probability maps were used to derive target regions for radiation therapy treatment planning. Methods and Materials: Two cohorts of patients with radio-recurrent PCa were used in this study. All patients underwent mp-MRI (T2 weighted, diffusion-weighted imaging, and dynamic contrast enhanced). A logistic regression model was trained using imaging features from 21 patients with biopsy-proven recurrence who qualified for