Aim To analyze the risk factor of the cardiac rupture (CR) in patients with acute ST-segment elevation myocardial infarction (STEMI). Based on this, the nomogram model of acute STEMI patients with CR was established. Methods Through Ningxia Medical University General Hospital's big data research platform and hospital information system retrieval, 5 412 patients with acute STEMI from January 2015 to December 2019 were continuously included in the study, of which 91 patients with CR were included as CR group; 5 321 patients non-combined with CR were included as non-CR group. LASSO regression, univariate and multivariate Logistic regression were used to analyze the risk factors of CR in patients with acute STEMI, and the CR nomogram predictive model was established. The nomogram model was validated and evaluated by using receiver operating characteristic(ROC) curve, Hosmer-Lemeshow test and clinical decision curve analysis (DCA). Results LASSO regression results showed that age, female, hypertension history, first medical contact time, shock index, Killip grade, white blood cell count, d-dimer, lactic acid, anterior myocardial infarction, β-blocker administration within 24 hours, angiotensin converting enzyme inhibitor/angiotensin receptor antagonist (ACEI/ARB) administration within 24 hours, emergency percutaneous coronary intervention (PCI) were 13 risk factors of CR (P＜0.05). The screened 13 risk factors were analyzed by univariate and multivariate Logistic regression, the results suggested that age, Killip grade, first medical contact time, white blood cell count, not undergoing emergency PCI and not taking ACEI/ARB drugs within 24 hours were the risk factors of CR in patients with acute STEMI. The acute STEMI with CR nomogram model was established according to the above 6 risk variables. The area under the ROC curve before and after the internal verification of the nomogram model was 0.946 (95%CI:0.927～0.961), 0.947 (95%CI:0.927～0.959), and the sensitivity was 0.957 and 0.904, respectively,the specificity was 0.858 and 0.876, respectively, which indicated that the model had good discrimination degree. The Hosmer-Lemeshow test showed that the deviation between the predicted value and the observed value was not statistically significant (χ²=12.70, P=0.122), indicating that the nomogram model had a good calibration. The DCA curve indicated that the predictive probability threshold of the model was from 0.00 to 0.40, and the clinical net benefit was the highest, indicating that the model had good clinical efficacy. Conclusion The nomogram model established in this study has better distinction, calibration and clinical effectiveness. It can effectively predict the probability of acute STEMI with CR, and provide some help for clinical diagnosis and treatment, so as to reduce the incidence of CR.