Undiagnosed chronic kidney disease (CKD) is common in people with diabetes mellitus. Validated noninvasive risk models are an attractive CKD screening option in diabetic patients to identify patients who are more likely to be diagnosed with CKD via biological tests. The study aimed to validate the Korean and Thai noninvasive CKD risk prediction models in African Type 2 diabetic patients. This was a hospital-based study. The Modification of Diet in Renal Disease (MDRD) and CKD Epidemiology Collaboration (CKD-EPI) equations were used to estimate the glomerular filtration rate (eGFR). CKD was defined as an eGFR <60 mL/min/1.73 m2, and any nephropathy as eGFR <60 mL/min/1.73 m2 and/or proteinuria. Discrimination was assessed and compared using c-statistics and non-parametric methods. Calibration performance was assessed before (original models) and after intercept adjustment. A total of 733 patients (421 men) aged 57.0 years (standard deviation = 10.4) were included. The MDRD equation identified 223 (30.4%) participants as having CKD and 377 (51.4%) participants with any nephropathy. The CKD-EPI equation identified fewer cases of CKD and any nephropathy with 194 (26.5%) and 357 (48.7%) cases, respectively. The original Korean model had the highest C-statistics of 0.696 (95% confidence interval: 0.654-0.739) for the outcome of eGFR <60 mL/min/1.73 m2 (using the CKD-EPI equation). Discrimination was significantly better in men, older and overweight participants. Intercept adjustment markedly improved calibration. Asian models have modest discrimination and good calibration with modest adjustment in predicting undiagnosed CKD in African diabetic patients; limiting their consideration for use in diabetes care in this setting.