Background: This study aimed to establish a non-invasive and simple screening model of coronary atherosclerosis burden based on the associations between multiple blood parameters and total plaque score (TPS), segment-stenosis score (SSS), coronary artery disease severity (CADS) in coronary artery disease (CAD) and thus reduce unnecessary coronary angiography (CAG).Methods: A total of 1,366 patients with suspected CAD who underwent CAG were included in this study.The clinical risk factors [age, gender, systolic blood pressure (SBP), diastolic blood pressure (DBP), total cholesterol (TC), high-density lipoprotein (HDL), triglyceride (TG), low-density lipoprotein (LDL), fasting plasma glucose (FPG), and glycated hemoglobin (GHB)] were collected. The presence of plaques and lumen stenosis was assessed based on CAG imaging. The TPS, SSS, and CADS were calculated, and the distribution spectrum of atherosclerotic plaques was described. Kruskal-Wallis test for multiple comparison tests was performed to analyze the differences in groups of different risk factors. The selected independent predictors were put into a multivariate logistic model, and the variables were further screened by stepwise regression to establish a screening model. Finally, the receiver operating characteristic (ROC) curve was used to evaluate the selected model's discriminant effect.Results: The distributions of TPS and SSS scores were both right-skewed. Among males, both TPS and SSS scores were higher than in females (χ 2 =46.7659, P<0.0001, χ 2 =51.6603, P<0.0001). Both TPS and SSS scores increased with age (χ 2 =123.4456, P<0.0001, χ 2 =123.4456, P<0.