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 γ equal to 27.321 2 and σ2 equal to 3.229 5. 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.