Objective: To investigate the influencing factors of atherosclerotic cardiovascular disease (ASCVD) in elderly patients with diabetes mellitus and to establish a predictive model. Methods: The clinical data of 68 patients with diabetes admitted to our hospital from February 2023 to October 2024 were retrospectively collected. According to whether the patients had diabetes combined with ASCVD, the patients were divided into simple diabetes and included in the control group. Diabetes mellitus combined with ASCVD was included in the trial group. Baseline data were collected and compared between the two groups. Logistic regression was used to analyze the influencing factors of diabetes mellitus combined with ASCVD, and the prediction model was constructed. Results: Among 68 elderly patients with diabetes, 41 patients with simple diabetes were included in the control group; Twenty-seven patients with diabetes combined with ASCVD were included in the trial group. There were no significant differences in mean age, alcohol consumption, diastolic blood pressure, high density lipoprotein cholesterol (HDL-C), total cholesterol (TC), triglyceride (TG) and albuminuria formula between the two groups (P>0.05). There were significant differences in gender, smoking, body mass index (BMI), fasting blood glucose, glycosylated hemoglobin, systolic blood pressure, low density lipoprotein cholesterol (LDL-C) and C-reactive protein (CRP) between the two groups (P<0.05). Logistic regression analysis showed that female, smoking, BMI>24.62 kg/m2, fasting blood glucose >7.46 mmol/L, glycosylated hemoglobin >6.83%, systolic blood pressure >141.79 mmHg, LDL-C>2.60 mmol/L, CRP>0.17 mg/dl were risk factors for ASCVD in diabetic patients (P<0.05). Prediction model construction: Logit (P) =-34.046+1.061× sex +0.951× smoking +0.226×BMI+0.940× fasting blood glucose +0.913× glycosylated hemoglobin +0.022× systolic blood pressure +1.180×LDL-C+1.456×CRP. ROC curve analysis results showed that the AUC of the predictive model for ASCVD in diabetic patients was 0.935, the sensitivity was 88.91, and the specificity was 80.52. Conclusion: Female, smoker, high BMI, high fasting blood glucose, high A1C, high systolic blood pressure, high LDL-C and high CRP are independent risk factors for ASCVD in elderly patients with diabetes, and the prediction model established by this method has good sensitivity and specificity, and can be used as a tool for early clinical prediction of ASCVD in elderly patients with diabetes.