Objective: To analyze the risk factors leading to infection after prostate biopsy，establish a nomogram prediction model and verify it. Methods: Clinical data of 523 patients who underwent ultrasound-guided prostate biopsy at our hospital during Jan.2023 and Jul.2024 were retrospectively analyzed.Patients were divided into an infection group and a non-infection group.Independent risk factors for infection after prostate biopsy were identified with univariate and multivariate binary logistic regression analyses，and a nomogram prediction model was constructed，which was validated with receiver operating characteristic (ROC) curve，calibration curve，and decision curve analysis (DCA). Results: Infection occurred in 54 cases (10.3%).Univariate and multivariate logistic regression analyses showed that age >65 years (OR=3.535，P=0.003)，diabetes (OR=5.693，P<0.001)，hypoproteinemia (OR=8.936，P<0.001)，preoperative urinary tract infection (OR=6.153，P<0.001)，puncture needles >12 (OR=4.347，P<0.001)，and transrectal puncture (OR=3.701，P<0.001) were independent risk factors for infection.Based on the multivariate logistic analysis results，a risk prediction nomogram model was constructed，with an area under the ROC curve (AUC) of 0.894.The calibration curve and DCA both indicated that the model had high predictive accuracy and clinical decision-making efficiency. Conclusion: Age >65 years，diabetes，hypoproteinemia，preoperative urinary tract infection，puncture needles >12，and transrectal puncture are independent risk factors for infection after prostate biopsy.The nomogram prediction model based on these factors helps identify high-risk patients，thereby enabling individualized treatment plans to reduce the incidence of infection.