Objective：A prognostic model was established based on clinical and ultrasonic omics features, and a nomogram was constructed to evaluate the long-term prognosis of patients with post-infarction left ventricular aneurysm (PI-LVA). Methods：Retrospective analysis of patients with PI-LVA admitted to the Department of Cardiovascular Medicine of Suining Central Hospital from July 2019 to May 2022. Combined with inclusion and exclusion criteria, 153 patients were finally selected and followed up, with the endpoint of all-cause mortality. Clinical variables were included in a multivariable Cox regression analysis to screen for risk factors associated with long-term prognosis. Echocardiograms of all patients were analyzed, and images of the apical two-chamber heart section during systole, including the complete wall aneurysm portion, were acquired. ITK-SNAP was used for segmentation to obtain the region of interest (ROI), and pyradiomics was used to extract ultrasonic omics features. Lasso regression was used for screening. A model was constructed based on clinical and ultrasonic omics features, and a nomogram was drawn for feasibility verification. Results：Multivariate Cox regression analysis showed that the Tp-Te interval, severe stenosis of the right coronary artery, and LVEF <35% were independent risk factors affecting the long-term prognosis of patients with PI-LVA. A total of 107 features were extracted from the ROI, and 3 significant features were selected by Lasso regression analysis. A prediction model was constructed based on 6 variables screened from clinical and imaging omics, and a nomogram was drawn. The consistency index of 1000 bootstrap corrections was 0.849 [95% CI (0.769-0.896)]. The area under the ROC curve at multiple time points of 24 months, 36 months, and 60 months was calculated to be 0.850, 0.831, and 0.898, respectively. The calibration curve showed good consistency between the predicted risk and the actual risk of the nomogram. The decision curve analysis showed that the nomogram had good clinical utility. Conclusion：The nomogram constructed based on clinical and ultrasonic omics features can effectively predict the long-term prognosis of patients with PI-LVA, providing potential guidance for clinical diagnosis and treatment.