Objective To examine the distribution of pathogens that cause postoperative nosocomial infections in patients with rectal cancer（RC） and to construct a predictive nomogram for nosocomial infection. Methods The clinical data of 1537 RC patients admitted to Sir Run Run Shaw Hospital between January 2021 and December 2022 were collected. Patients were assigned 1∶1 by propensity score matching（PSM） to the infection group（n=83） and control group（n=83） based on the occurrence of nosocomial infection. The distribution and drug resistance of bacteria in patients with nosocomial infection were analyzed. Risk factors for postoperative nosocomial infection were identified by least absolute shrinkage and selection operator（LASSO） regression，and a predictive nomogram was constructed using multivariate logistics regression. The predictive performance of the model was evaluated by receiver operating characteristic（ROC） curve，calibration curve，and decision curve analysis（DCA）. Results A total of 93 strains of pathogens were isolated from the 83 infected patients，including 62 strains of Gram-negative bacteria （66.67%；predominantly Escherichia coli and Pseudomonas aeruginosa），25 strains of Gram-positive bacteria（26.88%； mainly Enterococcus faecalis），and 6 strains of fungi（6.45%； all Candida albicans）. LASSO and multivariate logistics regression showed that smoking （odds ratio［OR］=3.97，95%CI=1.27-12.43），the dwelling time of drainage tube（OR=1.19，95%CI=1.08-1.30），difference in preoperative and postoperative neutrophil counts（OR=1.23，95%CI=1.01-1.49），and difference between preoperative and postoperative C-reactive protein levels（OR=1.05，95%CI=1.03-1.07） were independent risk factors for postoperative nosocomial infection in RC patients. The area under the ROC curve of the nomogram constructed based on the above factors was 0.933（95%CI=0.896-0.969）. The calibration curve showed that the predicted risk was in good agreement with the actual observed risk of infection. In addition，DCA demonstrated that the nomogram has good clinical utility and high net clinical benefits in predicting nosocomial infection. Conclusion The nomogram constructed in this study has a good predictive performance in postoperative nosocomial infection in RC patients.