Visible and near infrared (Vis/NIR) spectroscopy was applied for the fast determination of dynamic viscosity of automobile lubricant. One hundred fifty samples from 5 brands were collected for Vis/NIR spectral scanning. Partial least squares (PLS) analysis was applied as calibration method after preprocessing stage as well as a way to extract the first 6 principal components which were used as the input data matrix of least squares-support vector machine (LS-SVM) to develop the LS-SVM models. Radial basis function was used as core function with gamma equal to 27.3212 and sigma2 equal to 3.2295. The calibration set was composed of 125 samples, whereas 25 samples were in the validation set. The results indicated that LS-SVM model achieved the best prediction performance. A new process is proposed in this paper for determination of dynamic viscosity of automobile lubricant.