This study presented by Yu et al. presents the use of the SHap Additive exPlanations (SHAP) methodology to check on patients 1 year post-operation completed by the robot-assisted radical prostatectomy (RARP) for inguinal hernia risk. After the standard procedures for the RARP protocol, the robotic camera trocar is inserted above the umbilicus, following it to the rectus border. Instrumentation such as an endoscope, bipolar forceps, and monopolar scissors are used to perform adhesiolysis and identification of the pubic arches and transection of the vas deferens. This is followed by the dissection of the bladder neck, seminal vesicles, vas deferens through sharp and cold techniques. Reconstruction is completed with urethrovesical anastomosis, peritoneal closure, hemostasis checks, drain placement, and specimen retrieval. Out of the 652 patients that went through the procedures, 79 patients (12.1%) had developed inguinal hernias within 1 year of the operation while the rest did not experience complications. Post-operative urinary continence rates had gradually improved by the months and the hospital stay after surgery had a mean of 6.1 days. Model performance metrics displayed validation and independent test sets that prove the XGBoost model demonstrates superiority by having the highest accuracy (0.832) and highest specificity (0.884) showing optimal classification capability in finding negative cases. SHAP analysis of the XGBoost model showed age, BMI, preoperative albumin, T stage, and prior abdominal surgery as the most influential predictors of post-RARP inguinal hernia, with older age, advanced T stage, and surgical history increasing risk, while higher BMI and albumin were protective. This study is the first to apply ML and SHAP methodology to find a predictive model for the post-operative RARP inguinal hernias with success.