Objective To explore the predictive value of novel anthropometric indicators for the long-term prognosis in patients with acute myocardial infarction （AMI）. Methods A total of 712 patients diagnosed with AMI in the People's Hospital of Xinjiang Uygur Autonomous Region from January 2018 to December 2019 were selected as research subjects， and divided into an event group and a non-event group according to whether major cardiovascular adverse events （MACEs） occurred during the period of follow-up. Gensini score was used to quantitatively assess the degree of coronary artery stenosis. Spearman correlation analysis was used to explore the correlation between the new anthropometric indicators and Gensini score. Receiver operating characteristic （ROC） curve was used to evaluate the ability of new anthropometric indicators to predict MACEs， and the patients were grouped according to the optimal cut-off value. Kaplan-Meier curve was used to analyze the survival difference between the groups. Multivariate Cox regression was used to analyze the independent risk factors of MACEs. Results During a median follow-up of 27（20，39）months， a total of 125 patients developed MACEs. As compared with those in the non-event group， the patients in the event group had a higher proportion of hypertension， diabetes and abdominal obesity， higher HbA1c and FBG levels， and longer body weight and waist circumference. The LAP index， CMI index， BRI index and Gensini score were significantly increased， and the differences were statistically significant （P ? 0.05）. Spearman correlation analysis showed that LAP index， CMI index and BRI index were positively correlated with Gensini score （r = 0.233， 0.126， 0.272， P < 0.001）. ROC curve analysis showed that the AUC of LAP index， CMI index， VAI index， BRI index and ABSI index were 0.745， 0.640， 0.490， 0.874 and 0.506 respectively； Kaplan-Meier curve analysis showed that the cumulative incidence of MACEs in LAP index， CMI index and BRI index was significantly increased in the high-value group （Log-rank test， P ? 0.05）. The results of multivariate Cox regression analysis after adjusting confounding showed that CMI index （HR = 1.430， 95%CI： 1.049 ~ 1.952， P = 0.024） and BRI index （HR = 1.332， 95%CI： 1.234 ~ 1.439， P ? 0.001）were independent risk factors for MACEs. Conclusions CMI index and BRI index of new anthropometric indicators are independent risk factors for long-term prognosis in patients with AMI.