To realize the rapid identification of freshwater fish species,near infrared reflectance spectroscopy was employed to establish the identification models of fish species. 772 samples of 7 freshwater fish species (silver carp,grass carp,snakehead,crucian carp,common carp,black carp,bighead carp) were prepared to collect near infrared spectra data. The effects of preprocessing methods including standard normalized variate (SNV),multiple scattering correction (MSC) and the feature extraction methods including kernel principal component analysis (KPCA) and principal component analysis (PCA) on the discrimination models of support vector machine (SVM) were investigated,respectively. The results showed that the overall accuracy rate was 92.68% for the unknown sample after the SNV preprocessing and KPCA extraction of characteristic variables. Therefore,the SVM model constructed by near infrared spectroscopy combined with chemometric methods is feasible for rapid identification of freshwater fish species.