Objective To investigate the factors affecting carotid atherosclerotic plaque formation in elderly patients with diabetes mellitus and to develop a risk prediction model, providing a scientific basis for early clinical screening and personalized management.Methods This retrospective study included 120 elderly diabetic patients admitted to Gansu Rehabilitation Center Hospital from June 2022 to June 2024. Based on the carotid intima-media thickness (IMT), patients were categorized into the normal group (n = 21), thickened group (n = 28), and plaque group (n = 71). The clinical data of all patients were collected. Univariable analysis was performed to identify independent variables associated with carotid atherosclerotic plaques, followed by multivariable Logistic regression analysis to construct a risk prediction model. The predictive performance of the model was evaluated using the receiver operating characteristic (ROC) curve, and its accuracy and goodness of fit were assessed using a calibration curve.Results Significant differences were observed in the smoking index, stroke incidence, hypertension prevalence, HbA1c levels, TG/HDL-C ratio, TC/HDL-C ratio, LDL-C/HDL-C ratio, UACR levels, and FIB levels (P < 0.05). Stepwise multivariable Logistic regression analysis identified high smoking index [O^R = 4.871 (95% CI: 2.561, 9.266) ], history of stroke [O^R = 4.839 (95% CI: 1.151, 20.342) ], history of hypertension [O^R = 7.978 (95% CI: 2.026, 31.418) ], elevated HbA1c levels [O^R =2 .542 (95% CI: 1.272, 5.079) ], increased TG/HDL-C ratio [O^R = 16.001 (95% CI: 1.877, 136.432) ], increased TC/HDL-C ratio [O^R = 9.682 (95% CI: 2.369, 39.579) ], increased LDL-C/HDL-C ratio [O^R = 33.469 (95% CI: 6.347, 176.501) ], elevated UACR levels [O^R = 5.611 (95% CI: 1.288, 24.440) ], and elevated FIB levels [O^R = 4.212 (95% CI: 1.342, 13.218) ] as independent risk factors for carotid atherosclerotic plaques in diabetic patients (P < 0.05). Model validation showed a calibration error of 0.048, with the calibration curve closely matching the ideal curve. The area under the ROC curve (AUC) of the model was 0.970 (95% CI: 0.941, 0.999), with a sensitivity of 85.7% (95% CI: 0.756, 0.930) and a specificity of 97.2% (95% CI: 0.817, 0.999).Conclusion Higher smoking index, history of stroke and hypertension, and elevated levels of HbA1c, TG/HDL-C, TC/HDL-C, LDL-C/HDL-C, UACR, and FIB are major risk factors for carotid atherosclerotic plaques in elderly diabetic patients. The established risk prediction model demonstrates high sensitivity and specificity, offering effective support for early clinical screening and personalized management.