Abstract: OBJECTIVE To analyze the influencing factors of abdominal infection in patients with severe acute pancreatitis (SAP), and to develop an interactive nomogram model for predicting this complication. METHODS A total of 253 SAP patients admitted to the First Affiliated Hospital of Nanjing Medical University from Oct. 2023 to Aug. 2025 were enrolled, and their case data were collected. The patients were then divided into a training set (n=177) and a validation set (n=76) in a 7∶3 ratio. The training set was further divided into an infection group and a non-infection group based on the occurrence of abdominal infection. Univariate and multivariate logistic regression analyses were employed to screen the influencing factors of abdominal infection in SAP patients. The nomogram model was developed through R language. Finally, validation was performed for the model. RESULTS The incidence rate of abdominal infection was 35.59%. Logistic regression analysis showed that high Acute Physiology and Chronic Health Evaluation Ⅱ (APACHE Ⅱ) score, high CT Severity Index (CTSI) score, pancreatic necrosis, presence of abdominal effusion, prolonged intestinal paralysis and prolonged fasting duration were all risk factors for abdominal infection in SAP patients (all P<0.05). Receiver operating characteristic (ROC) analysis showed that the area under curve (AUC) value was 0.936 (95% CI: 0.890-0.968) in the training set model and 0.911 (95% CI: 0.830-0.962) in the validation set model. The calibration curve revealed that the predicted values of the nomogram model for abdominal infection in SAP patients were close to the actual values. CONCLUSION The nomogram developed in this study can assist in early clinical assessment and identification of high-risk SAP patients with concurrent abdominal infection, providing guidance for preventing disease progression.