Objective To explore the influencing factors of bleeding in ultrasound-guided percutaneous renal biopsy (PRB), construct a risk warning model, and analyze its clinical value. Method Seventy-two patients who underwent renal biopsy at Nanjing Hospital Affiliated to Nanjing Medical University and Lai’an Jianing Hospital were selected as the modeling group. They were divided into a bleeding group (32 cases) and a non-bleeding group (40 cases) based on whether they had bleeding. Baseline data, laboratory tests, and ultrasound examination data were collected from patients, and multiple logistic regression analysis was used to screen the influencing factors of postoperative bleeding in PRB, and a risk warning model was constructed. Another 64 patients who met the inclusion criteria were selected as the external validation group, and the receiver operating characteristic (ROC) curve was plotted to evaluate the predictive value of the model. Hosmer-Lemeshow goodness of fit test evaluates the degree of fit of the model.Perform internal and external validation of the model using the 10-fold cross validation method. Result The patients in the model group were compared for factors in terms of ultrasound skin pulp boundary，serum creatinine（Scr），glomerular filtration rate（eGFR），hemoglobin（Hb），platelets（PLT），IgA nephropathy（IgA N） and hypertensive nephropathy injury（HTN），and the differences were statistically significant（all P＜0.05）.Multivariate logistic regression analysis showed that the ultrasound skin pulp boundary was unclear，Hb＜110 g/L，PLT＜100×109/L，IgA N and HTN are risk factors for postoperative bleeding in PRB（all P＜0.05）.The area under the curve of the PRB postoperative bleeding risk prediction model group is 0.881，sensitivity is 81.25%，and specificity is 92.50%.The area under the curve of the external validation group is 0.837，sensitivity is 71.87%，and specificity is 90.00%.The Hosmer-Lemeshow goodness of fit test showed that the model had a good fit between the predicted probability and the actual probability in the modeling group and external validation group (P=0.6359, 0.2094). Conclusion The risk warning model constructed in this study has good predictive performance for postoperative bleeding in PRB, and can provide valuable reference and evaluation basis for the screening and prevention of high-risk populations in clinical practice.