Objective To establish nomogram model for individualized prediction of risk for pulmonary infection (PI) in elderly patients with acute myocardial infarction (AMI) after percutaneous coronary intervention (PCI), and verify the prediction efficiency of the model. Methods 215 elderly AMI patients who underwent PCI in a hospital from July 2018 to June 2021 were selected as the research object, clinical data of patients were collected, distribution of pathogens of post-operative PI was analyzed, risk factors for PI after PCI were conducted univariate, LASSO regression and multivariate regression analysis, and nomogram risk model was established. Results 39 patients had PI, infection rate was 18.14%, 43 pathogenic strains were isolated, 67.44% of which were Gram-negative bacteria. Multivariate regression analysis showed that age ≥70 years, smoking, diabetes mellitus, Killip grade III-IV, tracheal intubation and mechanical ventilation were independent risk factors for PI in elderly AMI patients after PCI (all P < 0.05). The model verification results show that C-index was 0.823; there was no significant difference in H-L deviation test results(χ²=4.122, P=0.537); the area under receiver operating characteristic curve was 0.840 (95%CI: 0.805-0.875); the net benefit predicted by the model was high in the range of 1%-96%, indicating that the model has good prediction efficiency. Conclusion Age ≥70 years old, smoking, diabetes mellitus, Killip grade Ⅲ-Ⅳ, tracheal intubation and mechanical ventilation are significantly associated with post-operative PI in elderly AMI patients after PCI, the nomogram model established based on this can be effectively predict the risk for PI.