Objective: To explore the independent risk factors of allogeneic blood transfusion during perioperative period of cytoreductive surgery in patients with ovarian cancer, and to construct a predictive model to facilitate clinical risk assessment and optimize perioperative blood management. Methods: Clinical data of 156 patients who underwent cytoreductive surgery for ovarian cancer in our hospital from January 2020 to December 2025 were retrospectively collected. The patients were divided into transfusion group (n=51) and non-transfusion group (n=105) according to whether they received allogeneic blood transfusion during perioperative period. The 1∶1 propensity score matching (PSM) was used to correct the confounding factors. Independent sample t test or Mann-Whitney U test was used for measurement data, and chisquare test was used for enumeration data. Variables with P<0.05 in univariate analysis were included in binary logistic regression for multivariate analysis to determine independent risk factors. A nomogram model for perioperative allogeneic blood transfusion risk prediction was constructed based on independent risk factors. Bootstrap method (100 samples) was used for internal calibration verification. ROC curve was used to evaluate the discrimination efficiency, and decision curve analysis (DCA) was used to evaluate the clinical net benefit of the model. Results: After propensity matching, the baseline data of the two groups were balanced and comparable. Multivariate logistic regression analysis showed that preoperative prothrombin time (PT) (OR=2.666, 95%CI 1.249~5.693, P=0.011), preoperative hemoglobin (Hb) (OR=0.953, 95%CI 0.923~0.984, P=0.003), intraoperative blood loss (OR=1.004, 95%CI 1.001-1.006, P=0.004), preoperative anemia grade (OR=3.052, 95%CI 1.007-9.252, P=0.049) were independent influencing factors of perioperative allogeneic blood transfusion. The nomogram model based on the above four factors was significant (LR χ =58.617, P<0.001), and the internal calibration curve showed that the predicted probability of the model was in good agreement with the actual probability (mean absolute error=0.042). The area under the ROC curve (AUC) was 0.890, indicating good discrimination efficiency. DCA showed that the clinical net benefit of the model was better than that of the unified transfusion/non-transfusion strategy in the 0-0.45 risk threshold range. Conclusion: Intraoperative blood loss, preoperative PT, preoperative Hb and preoperative anemia grade are independent risk factors for perioperative allogeneic blood transfusion in patients undergoing cytoreductive surgery for ovarian cancer. The nomogram model based on the above factors has good predictive efficacy and clinical hierarchical decision-making value, which can provide reference for clinical implementation of individualized blood management for high-risk patients and reduction of unnecessary blood transfusion rate.