Objective To investigate the risk factors for upper gastrointestinal bleeding in patients with hepatitis B-related cirrhosis (hereafter referred to as HBV-related cirrhosis) and establish a non-invasive predictive model.Methods Clinical data of 142 patients with HBV-related cirrhosis admitted to the First Hospital of Shanxi Medical University from January 2019 to December 2022 were retrospectively analyzed. Lasso regression was used to select effective predictive factors, and a logistic regression algorithm was employed to establish a nomogram predictive model. Internal validation of the model was performed using the bootstrap resampling method. The model was evaluated using receiver operating characteristic (ROC) curves, calibration curves (CA), and decision curve analysis (DCA), and the results were visualized.Results Among the 142 patients with HBV-related cirrhosis, 100 cases experienced upper gastrointestinal bleeding. The optimal modeling indicators selected by Lasso regression were gender, hemoglobin, neutrophil percentage, blood glucose, spleen longitudinal diameter, and portal vein diameter. The ROC curve showed that the sensitivity of the nomogram model was 96.0%, the specificity was 83.0%, and the area under the ROC curve (AUC) was 0.969 (95% CI: 0.946, 0.993), higher than the MELD score of 0.592 (95% CI: 0.487, 0.698) and CTP score of 0.623 (95% CI: 0.509, 0.738). The CA curve indicated good agreement between the predicted and actual probabilities of the model, and the DCA curve suggested that the use of the nomogram model could increase the net benefit for patients.Conclusion The nomogram model constructed based on gender, hemoglobin, neutrophil percentage, blood glucose, spleen longitudinal diameter, and portal vein diameter has good predictive efficacy and clinical application value for predicting upper gastrointestinal bleeding in patients with HBV-related cirrhosis.