Objective To explore the correlation between Chinese visceral adipose index (CVAI) and visceral fat area (VFA) with diabetes nephropathy (DN) in Chinese population, and their values of early warning. Methods Clinical data of 240 patients with type 2 diabetes (T2DM) hospitalized in the Department of Endocrinology of Gansu Provincial People's Hospital from October 2020 to October 2021 were retrospectively analyzed, including the baseline characteristics, physical examination findings, and biochemical indicators. They were divided into DN group (n=114) and non-DN group (n=126) according to the presence or absence of DN. The correlation between CVAI and VFA with urinary albumin excretion rate (UAER), urinary albumin-to-creatinine ratio (UACR), and estimated glomerular filtration rate (eGFR) was assessed by the Spearman’s correlation test. Independent risk factors of DN in T2DM patients were screened by multivariatestepwise logistic regression analysis, and a multivariate logistic regression model was created. The predictive value of the model and each risk factor was evaluated by plotting the receiver operating characteristic (ROC) curve. Results Compared with those of the non-DN group, patients in DN group presented significantly longer duration of diabetes, larger weight, body mass index, waist circumference, hip circumference, waist height ratio, waist hip ratio, and neck circumference, and higher fasting plasma glucose (FPG), urinary albumin excretion rate (UAER), urine albumin-creatinine ratio (UACR), glycosylated hemoglobin(HbA1c), lipid accumulation production, CVAI, VFA and subcutaneous fat area, and lower estimated glomerular filtration rate (eGFR) (all P<0.05). Spearman’s correlation test showed that UAER and UACR were positively correlated with CVAI and VFA (all P<0.05). Logistic regression analysis showed that CVAI, VFA, FPG and the course of diabetes were independent risk factors for DN in T2DM patients (all P<0.05). ROC curve analysis showed that the area under the curve (AUC), sensitivity and specificity of CVAI were 0.6730, 0.3947, and 0.881, respectively, which of VFA were 0.6453, 0.7456, and 0.4921, respectively. Besides, AUC, sensitivity and specificity of the created logistic regression model were 0.7493, 0.7368, and 0.6825, respectively. The predictive potential of the logistic regression model was better than that of a single independent risk factor. Conclusion CVAI, VFA, FPG and the course of diabetes are independent risk factors for DN in T2DM patients. CVAI and VFA can be used as early warning indicators for DN in T2DM patients, providing an important basis for the management of visceral obesity patients.