Excessive accumulation of body fat (BF) promotes obesity, whilst posing a significant health hazard. There being no agreed, optimal quantifying methods, application of BF variable in clinical practice is not deemed an effective assessment option. The study, involving 4,735 patients (33.6% men), aged 45-64, aimed to identify optimal cut-off values for anthropometric indicators of obesity to evaluate cardiometabolic risk. A minimum P-value approach was applied to calculate the cut-offs for BF%. Threshold values for body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height (WHTR) ratio, facilitating optimal differentiation of cardiometabolic risk, were based on BF%, expressed as a binary classifier. The newly estimated cut-off values for predicting cardiometabolic risk, based on BMI, were lower than the referential obesity thresholds, whereas the threshold values of WC, WHR, and WHTR were higher. Apart from dyslipidemia, the odds of cardiometabolic disorders were higher, when the anthropometric indicators under study exceeded the cut-off points in both sexes. The proposed cut-offs proved instrumental in predicting cardiometabolic risk, whilst highlighting diagnostic and clinical potential of BF%, whereas BMI boasted the highest predictive potential. Cardiometabolic risk also proved significantly higher even in the overweight patients.