The possibility of using near-infrared reflectance spectroscopy (NIRS) for quantitative determination of 8 important nutrient compositions, including moisture, crude protein, ether extract, ash, total phosphorus, neutral detergent fiber, acid detergent fiber and crude fiber in corn DDGS was investigated in the present study. Ninety-three samples were collected from 18 plants in China over a three years period. Calibrations were performed by modified partial least squared algorithm and 15 different derivatives plus scatter correction spectral pretreatments. The results showed that the second derivative mathematical treatment gave the best prediction performance for most constituents. The prediction performance of models developed using 93 calibration samples was better than that developed using 70 samples. The coefficients of determination for calibration (RSQcal), coefficients of determination for cross-validation (1-VR), and RPDCV of cross-validation in models developed using 93 samples were 0.94～0.99, 0.89～0.99, and 2.98～14.85, respectively. These results indicate that NIRS can be used as a quantitative method for rapid determination of nutrient composition in corn DDGS.