In order to determine the influence of key morphological traits on the body weight (BW) of three-line hybridizations (SCDF₃, SDCF₃) and the F3 generations of their parent populations (Dianshan Lake, DSF₃; Dongting Lake, DTF₃; Yangtze River, CJF₃) of Macrobrachium nipponense, the correlations between morphometric attributes and BW were explored using correlational, path, and regression analyses. Thirty individuals from each of the five populations were randomly sampled to measure their BW and 12 morphometric attributes, including the body length (BL), overall length (OL), rostrum length (RL), second pereiopod length (P₂L), carapace length (CL), carapace width (CW), sixth abdominal segment length (A₆L), sixth abdominal segment height (A₆H), abdomen length (AL), telson length (TL), number of upper frontal eminence spin (NUS), and number of lower frontal eminence spin (NLS). Correlation coefficients among all variables were calculated. Path coefficients were calculated by setting the BW as a dependent variable and other attributes as independent variables via stepwise elimination. The results showed that, except for those of the NUS and NLS, the correlations of the 10 other morphological traits were very significantly positively correlated with BW (P＜0.01). The multiple correlation coefficients between morphological traits and body mass of five populations were as follows: 0.935 for DSF₃, 0.906 for DTF₃, 0.902 for CJF₃, 0.958 for SCDF₃, and 0.988 for SDCF₃. The path coefficients showed that: (1) The CW, OL, P₂L, and TL of the Dianshan Lake population were significantly correlated with BW, and the multiple regression equation for the estimation of BW was Y_DSF3=−9.661+CW×0.365+OL×0.078+P₂L×0.32+TL× 0.28; (2) The CW, AL, and A6H of the Dongting Lake population were significantly correlated with BW, and the multiple regression equation for the estimation of BW was Y_DTF3=−7.009+CW×0.448+AL×0.129+A₆H×0.633; (3) The BL and RL of the Yangtze River population were significantly correlated with BW, and the multiple regression equation for the estimation of BW was Y_CJF3=−11.795+BL×0.258+RL×0.104; (4) The BL, A₆H, and P₂L of the SCDF₃ population were significantly correlated with BW, and the multiple regression equation for the estimation of BW was Y_SCDF3=–4.402+BL×0.093+A₆H×0.531+P₂L×0.013; (5) The P₂L, BL, and CL of the SDCF₃ population were significantly correlated with BW, and the multiple regression equation for the estimation of BW was Y_SDCF3=–2.861+P₂L×0.029+BL×0.062+CL×0.078. The clustering results showed that the progenies of the two hybrid populations were most similar in morphology. The results of this study can provide reference for the breeding of M. nipponense and the conservation and utilization of its germplasm resources.