Alfalfa hay has high nutritive value, and it is one of the most important protein feed for domestic animals. The quality parameters of alfalfa hay, including CP, Ash, NDF, ADF, ADL and IVDMD, were predicted using Fourier transform near infrared reflectance spectroscopy with PLS regression in this test. Then the 6 models were validated by cross-validation and external-validation. The results indicated that FT-NIR models of alfalfa hay quality have considerable accuracy and precision: the correlation coefficient of cross-validation is 0.953 88 to 0. 990 19, and the RMSECV is 1.980-0.345; The correlation coefficient of external-validation is 0.963-0. 990. By using FT-NIR, analysis can rapidly and accurately determine the quality of alfalfa without any chemical reagent. This method is of great significance for analysing the trait of alfalfa production, the quality determination, the estimation of germ plasm resource, and the identifying and selecting of hybridized generations in alfalfa research of China.