Based on Euclidian distances between synchronous two-dimensional infrared correlation spectra, in terms of the average Euclidian distances between unknown samples and “extreme samples”, and average intra- and inter- Euclidian distances of samples in the calibration set, a new method for the discrimination of adulterated milk was proposed. Sixteen pure milk samples were collected and 16 adulterated milk samples with urea (0.01～0.3 g·L-1), and 16 adulterated milk samples with melamine (0.01～0.3 g·L-1) samples were prepared, respectively. The IR absorption spectra of all samples were measured at room temperature. The synchronous two-dimensional correlation spectra were generated from concentration-dependent spectral variation of adulterant in milk. The Euclidian distances were calculated between synchronous two-dimensional infrared correlation spectra of all samples. Then, the classification models were built respectively for adulterated milk with urea, and adulterated milk with melamine. The “extreme samples”, average intra- and inter- Euclidian distances were determined. Finally, the unknown samples in prediction set were predicted using constructed models in terms of classification rules of adulterated milk. The classification accuracy rates for pure milk and adulterated milk were 100%. The effectiveness of the proposed method was verified. The results obtained in this study revealed that synchronous two-dimensional infrared correlation spectra in combination with Euclidian distance has a feasible potential to discriminate adulterated milk and pure milk.