A total of 96 red wines aged with 3 kinds of methods were included in this study, including 44 wines aged in oak barrel, 26 wines aged in stainless steel tank added with oak chips and 26 wines aged in stainless steel tanks. The infrared spectra of the wines were scanned by Fourier transform infrared spectrometer with attenuated total reflection (ATR) accessories. To classify the 96 different aged wines, discriminant partial least squares (DPLS) method and support vector machine (SVM) method were used to establish models respectively. In order to examine the stability of the discriminant model, modeling was repeated 10 times with two-thirds of samples randomly selected as cross-validation. All the models had high discriminating power with the classification accuracy of the cross-validation and the validation all higher than 90%. These results suggest that the infrared ATR spectroscopy combined with pattern recognition method is a promising tool for discriminating different aging wines.