Objective To discuss the correlation among monocyte to high-density lipoprotein cholesterol ratio (MHR), triglyceride-glucose (TyG) index, and chronic kidney disease (CKD) in the community-dwelling elderly population, and to evaluate the predictive value of a multivariate joint prediction model based on MHR, TyG index combined with uric acid, body mass index (BMI), and age for CKD in the elderly. Methods Clinical data and peripheral blood test results were collected from a total of 1 653 elderly individuals in the Lujiazui community of Pudong New Area, Shanghai, in 2022. Based on the estimated glomerular filtration rate (eGFR), the study population was divided into a non-CKD group [eGFR≥60 mL/(min·1.73 m²)] and a CKD group [eGFR<60 mL/(min·1.73 m²)]. The predictive value of the combined MHR-TyG model for CKD in the elderly was analyzed. Results Logistic regression analysis showed that age, BMI, uric acid, MHR, and TyG index were all independent risk factors for CKD (all P<0.05). Restricted cubic spline (RCS) curves and mediation analysis demonstrated that MHR was significantly non-linearly and positively associated with the risk of CKD (P for overall<0.001, P for nonlinear=0.016). When MHR>0.3, the risk of CKD increased significantly. The proportion of the mediation effect of MHR was 23.88% in the relationship between BMI and CKD, and 4.77% in the relationship between age and CKD. Receiver operating characteristic (ROC) curve analysis showed that the combined MHR-TyG prediction model achieved an area under the curve (AUC) of 0.826 (95% CI: 0.793–0.859, P<0.001), with a sensitivity of 79.1% and a specificity of 73.4%, demonstrating predictive performance superior to any single indicator. Subgroup analysis suggested that MHR remained a significant predictor in non-high-risk populations, such as those with normal BMI, uric acid, and triglyceride levels. Conclusions Age, BMI, uric acid, MHR, and TyG index are all independent risk factors for CKD. The risk prediction model constructed by combining MHR-TyG with age, BMI, and uric acid has good predictive performance and is superior to any single indicator.