Objective：This study aims to analyze the risk factors of patients with premature ST segment elevation myocardial infarction(STEMI)and to develop a nomogram model to predict the risk of postoperative major adverse cardiac events(MACE)in patients with premature STEMI. Methods：A total of 166 patients diagnosed with premature STEMI undergoing percutaneous coronary intervention(PCI)in the Affiliated Huaian No.1 People’s Hospital of Nanjing Medical University from January 2017 to December 2018 were selected as the research subjects，and they were followed up for 24 months. According to the occurrence of MACE，they were divided into MACE group(62 cases)and non-MACE group(104 cases). Risk factors were screened using LASSO regression with Cox regression analysis，and a nomogram prediction model was constructed. The efficacy of the model was evaluated by receiver operating characteristic curve(ROC)，clinical decision curve(DCA)，calibration curve，etc.，and the stability of the model was verified by Bootstrap self sampling. Results：The results of LASSO regression and Cox regression showed that neutrophil gelatinase associated lipocalin(NGAL)，creatinine，time from AMI to opening of infarct related artery，left ventricular ejection fraction(LVEF)，infarct related artery were significant risk factors for the occurrence of postoperative MACE in patients with premature STEMI(P ＜ 0.05)，and the nomogram prediction model was constructed using these 5 predictors. The areas under the ROC curves of the models were 0.95 (95% CI：0.89~1.00)，0.94(95% CI：0.80~0.99)，0.87(95% CI：0.82~0.93)at 6，12，24 months after PCI，respectively，which were larger than those of the individual risk factors. The calibration curve is close to the ideal curve. The DCA curves showed better performance of the nomogram prediction model in the 0.25~1 threshold probability range. Conclusion：In this study，a nomogram prediction model was constructed based on the significant risk factors for the occurrence of MACE after PCI in patients with premature STEMI，and after Bootstrap internal validation，the prediction model had better efficacy and stability，and could accurately predict the risk of MACE at 6，12，and 24 months after PCI in patients with premature STEMI. It is helpful to carry out individualized intervention treatment for high-risk patients with premature STEMI and improve their prognoses.