Background/Objectives: This study evaluates whether combining 68Ga-PSMA-11-PET/CT derived imaging biomarkers with clinical risk factors improves the prediction of early biochemical recurrence (eBCR) or clinical progress in patients with high-risk prostate cancer (PCa) after primary treatment, using machine learning (ML) models. This evidence concerns the gene FOLH1 and prostate carcinoma.