Objective To develop a predictive model for selecting patients with high-risk localized prostate cancer（HRLPC） who are suitable for preoperative maximum androgen blocking（MAB） therapy. Methods This study was conducted among 96 patients with HRLPC who were diagnosed based on transrectal biopsy and underwent radical prostatectomy in Department of Urology，The First Affiliated Hospital of Chongqing Medical University，from January 1，2021 to June 30，2024，and all patients received MAB therapy for 3 months before surgery and were followed up for 6 months after surgery. Related data were collected from all patients，including baseline demographic features，laboratory data，imaging findings，perioperative data，and follow-up information. At first，the association between prostate-specific antigen density（PSAD） stratification after MAB therapy and pathological and biochemical benefits was analyzed to determine the optimal PSAD group，then machine learning was used to identify important variables and establish a predictive model，and finally，the model was evaluated using the ROC curve，the calibration curve，and clinical applicability assessment. Results The low PSAD group ［PSAD <0.17 ng/（mL∙cm³）］ showed the best results of perioperative outcomes，pathological downgrading，the rate of undetectable PSA after -surgery，recovery from urinary incontinence，and PSA follow-up（P<0.05）. The model was established based on prostate volume，low-density lipoprotein cholesterol，PSAD，smoking history，total cholesterol，PSA，and body mass index，and this predictive model had good performance （with an area under the ROC curve of 0.769） and showed a certain degree of clinical applicability. Conclusion Patients in the low PSAD group tend to have better pathological and biochemical benefits. This study provides a reliable predictive model to assist in the individualized treatment of patients with HRLPC.