Objective To investigate the role of coronary artery computed tomography angiography (CCTA) in identifying the plaque characteristics and prognosis in the elderly patients with acute coronary syndrome (ACS). Methods A retrospective analysis was made of the clinical data of 208 elderly patients with suspected coronary heart disease (CHD) admitted to the Chest Pain Center of Qionghai People′s Hospital of Hainan Province from February 2021 to December 2022. Among them, 58 ACS patients were included in the ACS group. According to their gender, age and cardiovascular risk factors (smoking history, hypertension, diabetes, blood lipid levels, etc.), another 58 patients with stable angina pectoris (SAP) were selected as a SAP group using the propensity score matching method (1∶1 ratio) during the same period. All patients underwent CCTA examination, and the two groups were compared in plaque characteristic indexes such as plaque length, calcified plaque (CP) volume, non-calcified plaque (NCP) volume, total plaque volume, CP load, NCP load, and total plaque load. In addition, 58 ACS patients were divided into major adverse cardiovascular events (MACEs) group (n=15) and non-MACEs group (n=43) based on prognosis. Patients with different prognosis were compared in the plaque characteristic indexes on CCTA. SPSS statistics 22.0 was used for data analysis. Depending on the data type, t test orχ² test was used for comparison between groups. Pearson analysis was performed for the correlation between blood lipid levels and plaque characteristic indexes. Receiver operating characteristic (ROC) curve was used to analyze the predictive value of each plaque characteristic index on ACS and MACEs. Results Plaque length, NCP volume, and NCP load in the ACS group were significantly higher than those in the SAP group, with statistically significant differences (P<0.05). The MACEs group had significantly higher plaque length, NCP volume, and NCP load than the non-MACEs group, with statistically significant differences (P<0.05). Pearson correlation analysis showed that serum low-density lipoprotein cholesterol (LDL-C) was positively correlated with plaque length (r=0.463), CP volume (r=0.246), NCP volume (r=0.414), total plaque volume (r=0.292), CP load (r=0.251), NCP load (r=0.392), and total plaque load (r=0.215; all P<0.05). The ROC curve analysis showed that patch length, NCP volume and NCP load had good predictive value for ACS with area under the curve (AUC) of 0.843 (95%CI 0.761-0.925), 0.814 (95%CI 0.703-0.926) and 0.721 (95%CI 0.573-0.869); optimum cutoff value of 19.19 mm, 152.99 mm³ and 42.56%; sensitivity of 91.67%, 91.67% and 66.67%, and specificity of 75.00%, 63.54% and 77.08%, respectively (P<0.05). Patch length, NCP volume, and NCP load demonstrated good predictive value for MACEs, with AUC of 0.694 (95%CI 0.515-0.876), 0.711 (95%CI 0.502-0.920) and 0.735 (95%CI 0.551-0.919); optimum cutoff value of 21.02 mm, 169.62 mm³ and 45.37%; sensitivity of 77.78%, 66.67% and 88.89%, and specificity of 59.18%, 85.71% and 61.22% (P<0.05). Conclusion The plaque characteristic indexes on CCTA not only have good diagnostic value but also can effectively predict the occurrence of MACEs in the elderly ACS patients within one year.