Objective To analyze the risk factors of post-operative infection in patients with liver cancer after hepatectomy, and construct a predictive model for post-hepatectomy infection. Methods Patients who underwent hepatectomy in the First Affiliated Hospital of Soochow University from February 2017 to October 2019 were retrospectively analyzed. General data, laboratory data, operation data and post-operative infection of patients were investigated. Univariate χ² test and multivariate logistic regression were used to determine the independent risk factors for post-operative infection. Based on independent risk factors, logistic risk predictive model was constructed. The area under the receiver operating characteristic (ROC) curve was used to evaluate the predictive effect of the model. In addition, 100 cases of liver cancer patients undergoing surgical resection from January to June in 2020 were selected to establish the validation group, data of modeling group were verified. Results A total of 310 patients were inclu-ded in analysis, 45 cases of healthcare-associated infection (HAI) developed after operation, incidence of HAI was 14.52%, there were 15 cases (33.33%) of surgical site infection, 12 cases (26.67%) of peri-hepatic infection and 18 cases (40.00%) of other distant site infection. Serum albumin (ALB) < 35 g/L, operation time>240 minutes, blood transfusion volume >1 000 mL, drainage time>7 days, ASA score>grade II were independent risk factors for post-operative infection in patients with liver cancer. According to risk factors, risk predictive model was constructed. The area under the ROC curve of predictive model was 0.904, sensitivity, specificity and Youden index were 0.889, 0.766 and 0.655 respectively. Conclusion The model has a good predictive effect on post-operative infection in liver cancer patients after hepatectomy, which can provide a theoretical basis for clinical medical staff to prevent infection in high-risk groups.