Objective To investigate the value of homocysteine (Hcy) combined with carotid artery ultrasound parameters in predicting the degree of coronary artery stenosis in patients with coronary heart disease. Methods A total of 92 patients with coronary heart disease who were admitted to our hospital from February 2021 to February 2023 were enrolled, and according to the Gensini score, they were divided into mild group with 53 patients and moderate-to-severe group with 39 patients. A univariate analysis was used to investigate the association of general information, Hcy, and carotid artery ultrasound parameters (carotid intima-media thickness [IMT] and carotid plaque Crouse score) with the degree of coronary artery stenosis in patients with coronary heart disease, and a multivariate analysis was used to identify the risk factors for the degree of coronary artery stenosis. The receiver operating characteristic (ROC) curve was plotted to investigate the value of Hcy, IMT, and carotid plaque Crouse score in predicting the degree of coronary artery stenosis in patients with coronary heart disease. Results Compared with the mild group, the moderate-to-severe group had significantly higher Hcy (17.89±2.46 μmol/L vs 13.41±2.15 μmol/L, P<0.05), IMT (1.41±0.39 mm vs 1.01±0.26 mm, P<0.05), and carotid plaque Crouse score (3.28±0.57 vs 1.79±0.32, P<0.05). The multiple linear regression analysis showed that Hcy, IMT, and carotid plaque Crouse score were high-risk factors for the degree of coronary artery stenosis in patients with coronary heart disease (P<0.05). The ROC curve analysis showed that the combination of Hcy, IMT, and carotid plaque Crouse score had an area under the ROC curve (AUC) of 0.927 (95% confidence interval [CI]: 0.869-0.985) in predicting the degree of coronary artery stenosis in patients with coronary heart disease, while the three indicators alone had an AUC of 0.854 (95%CI: 0.777-0.931), 0.800 (95%CI: 0.701-0.899), and 0.863 (95%CI: 0.788-0.938), respectively. Conclusion Hcy combined with carotid ultrasound parameters can effectively predict the degree of coronary artery stenosis in patients with coronary heart disease and thus has a certain application value. Therefore, it holds promise for clinical application.