The quantitative method named moving window partial least square (MWPLS) is applied to predicting the content of Cd in navel orange by analyzing the spectral information obtained by laser induced breakdown spectroscopy (LIBS). Five methods like standard normal variate (SNV), first derivative (FD), second derivative (SD), centralization and multivariate scatter correction (MSC) are utilized to process LIBS data and acquire better spectral quality, and the window width of MWPLS is optimized to select the area of wavelength correlated with Cd element. Meanwhile, MWPLS is compared with conventional partial least square method. The results display that the model built by FD is better when moving window is 61 wavelength wide and the range of wavelength is 218.61-222.55 nm. At this condition, the determinant coefficient of validation set, root mean square error of prediction (RMSEP), principal component and average relative error are 0.9953, 15.10×10-6, 12 and 7.43%, respectively. This study shows that the LIBS area for predicting Cd in navel orange can be screened by MWPLS coupled with suitable data preprocessing, and the prediction ability can be improved effectively.