The rapid determination of the value of cetane is important for the determination of the quality of diesel. To remove the absolute noises of the spectra, the extracted 381 absorbance spectra were preprocessed with Savitzky-Golay smoothing (SG), EMD, and Wavelet Transform (WT) methods. The preprocessed spectra were then used to select sensitive wavelengths with competitive adaptive reweighted sampling (CARS). LS-SVM were applied to build models with the selected 12 wavelength variables. The overall results showed that the LS-SVM models with the selected wavelengths based on WT preprocessed spectra obtained the best results with the determination coefficient (r2) and RMSEP were 0723 and 1878% for prediction set. The results indicated that it was feasible to use NIR with characteristic wavelengths which were obtained with CARS variable selection method, combined with LS-SVM calibration could apply for the rapid and accurate determination of diesel cetane. Moreover, this study laid a foundation for further implementation of online analysis of cetane and rapid determination of other diesel quality parameters.