This work aimed to use attenuated total reflectance Fourier transform infrared spectroscopy to identify the lavender essential oil by establishing a Lavender variety and quality analysis model. So, 96 samples were tested. For all samples, the raw spectra were pretreated as second derivative, and to determine the 1 750~900 cm-1 wavelengths for pattern recognition analysis on the basis of the variance calculation. The results showed that principal component analysis (PCA) can basically discriminate lavender oil cultivar and the first three principal components mainly represent the ester, alcohol and terpenoid substances. When the orthogonal partial least-squares discriminant analysis (OPLS-DA) model was established, the 68 samples were used for the calibration set. Determination coefficients of OPLS-DA regression curve were 0.959 2, 0.976 4, and 0.958 8 respectively for three varieties of lavender essential oil. Three varieties of essential oil's the root mean square error of prediction (RMSEP) in validation set were 0.142 9, 0.127 3, and 0.124 9, respectively. The discriminant rate of calibration set and the prediction rate of validation set had reached 100%. The model has the very good recognition capability to detect the variety and quality of lavender essential oil. The result indicated that a model which provides a quick, intuitive and feasible method had been built to discriminate lavender oils.