The non-invasive lubricant acid value measurement method based on a visible and near-infrared spectroscopy is studied. The visible and near-infrared spectra of the lubricant in the region from 475 nm to 975 nm are obtained. A visible and near-infrared spectral detection model is established by using a least square support vector machine. By combining the uninformative variable elimination with the successive projection algorithm, effective spectral wavelengths are selected. Among the 500 variables, only eight wavelength variables namely 498 nm, 553 nm, 591 nm, 874 nm, 893 nm, 910 nm, 935 nm and 951 nm are selected. The least square support vector machine model based on those eight wavelength variables has obtained a prediction set of 0.9546, a root mean square error of 0.0081 and a residual predictive deviation of 4.5663. This prediction result shows that the visible and near-infrared spectroscopy can be used to measure the acid value of lubricant non-invasively. Compared with the standard acid value measurement method, it has the advantages of fastness, non-invasion and low cost. Meanwhile, it is also an effective algorithm for spectral variable selection.