Background <p>The combination of percutaneous coronary intervention (PCI) and veno-arterial extracorporeal membrane oxygenation (VA-ECMO) has become a widely used approach for resuscitating patients with acute myocardial infarction (AMI) complicated by cardiac arrest (CA). Nonetheless, limited research has focused on predicting in-hospital mortality in affected patients. This study aims to identify factors associated with in-hospital mortality and develop a clinical prediction model for these patients.</p> Methods <p>Clinical presentations of AMI patients with CA undergoing PCI supported by VA-ECMO at two hospitals in Zhengzhou were evaluated. Patients were stratified based on their survival status at discharge. A comprehensive analysis, which included univariate logistic regression, LASSO regression, and multivariate logistic regression, was conducted to identify predictors and develop a nomogram for in-hospital mortality. The nomogram's predictive performance was subsequently compared to that of existing models.</p> Results <p>The study included 139 patients, of whom 84 died during hospitalization. Using factors such as age, current smoking, left main culprit vessel, lactic acid levels, and serum creatinine, a nomogram model was developed. The model demonstrated good predictive performance, with an area under the curve of 0.826 (95% CI 0.757–0.894) in the training dataset and 0.783 (95% CI 0.706–0.859) in the internal validation dataset, indicating high accuracy and stability. Clinical decision curve analysis confirmed the model’s utility, particularly for risk thresholds above 20%, outperforming existing models.</p> Conclusions <p>This study identified independent predictors of in-hospital mortality in AMI patients with CA undergoing PCI supported by VA-ECMO and developed a clinically applicable prediction model.</p>