Aim of this study was to identify the physical and strength profile of Indian elite rowers categorically and finding relation of those variables with rowing performance. The study also aimed to develop rowing performance predicting different regression models to specify their essential performance limiting elements that could be used to maximize performance. To fulfill the research purpose, 139 light weight category and 60 open category elite male rowers with more than five years of rowing experience were evaluated. Height, weight, skin caliper, sliding caliper and strength dynamometer, respectively. Body fat percentage was calculated with Siri's equation and somatotype using Heath-Carter formula. A 2000m rowing test was conducted on a rowing ergometer. Results showed higher body weight (10.3%,p<0.0001), height (1.9%,p<0.0001), age (8.2%,p<0.01), body fat percentage (18.2%,p<0.0001), endomorph (30.3%,p<0.0001), mesomorph (17.8%,p<0.0001), back strength (8.9%,p<0.0001), right hand grip strength (5.8%,p<0.001), left hand grip strength (6.5%,p<0.001), less ectomorph (14.1%,p<0.001) and less time to finish 2000m (2.2%,p<0.0001) in open category rowers than light weight category. The 2000m rowing time was significantly (p<0.001) correlated with age (r=-0.459), height (r=-0.340), weight (r=-0.506), back strength (r=-0.458), right hand grip strength (r=-0.311) and left hand grip strength (r=-0.333). Body fat percentage (r = 0.191) and mesomorphic somatotype (r=-0.223) were correlated significantly (p<0.05) with performance. Multiple regression analysis identifies age, height, weight and body fat percentage as strong predictors of 2000m rowing ergometer performance (R=0.730). Combining strength components with the above is also a good predictor of 2000m rowing time (R=0.704). 2000m time(s)=519.211-0.480x age+0.111x height-1.836x weight+1.503x body fat%+0.010x back strength-0.099x right hand grip strength-0.075x left hand grip strength. In this context, these decisive physical and strength variables can be used to predict performance, improving training capability and identifying talents.