Introduction: Body mass index (BMI) has traditionally been the chosen indicator by which to measure body size, composition, and to diagnose underweight and overweight. However, alternative measures that reflect abdominal adiposity, such as waist circumference, waist–hip ratio and waist–height ratio, have been suggested as being superior to BMI in predicting cardio-vascular diseases (CVD) risk. This study was aimed at determining the predictive power of anthropometric indicators like body mass index, waist circumference and waist stature ratio with body fat in an Indian military personnel population group, and to establish cut-off points as discriminators of high body fat. Methods: The study was crosssectional in nature with a sample size of 388 active Gorkha male personnel aged 20-49 years (mean age 33.1±5.33). Anthropometric indicators included body mass index, waist circumference, waist-hip ratio and waist-stature ratio. The analysis of receiver operating characteristic curves (ROC) with a confidence interval of 95% was adopted to identify predictors of obesity. Subsequently, the cut-off points with their relevant sensitivities and specificities were identified. Result: Areas under the ROC curves with 95% confidence intervals were body mass index = 0.86 (0.84-0.88); waist circumference = 0.82 (0.80-0.84); waist- hip ratio = 0.74 (0.71-0.77); waist-stature ratio = 0.81 (0.78-0.84). Different cut-off points of anthropometric indicators with better predictive power and their relevant sensitivities and specificities were identified. The following cut-offs with their corresponding sensitivity and specificity values are suggested for determining obesity for the study population: body mass index= 23.4 (98.00, 62.00), waist circumference= 77.8 (98.00, 60.50) and waist stature ratio= 0.47 (98.60, 68.00) respectively. Conclusion: The results showed that among active military personnel, BMI, WC and WSR may serve well in classifying individuals into broad categories corresponding to percentage fat categories. Further studies on different populations should be undertaken for the verification of the cut-off levels identified.