Visible and near infrared reflectance spectroscopy (Vis/NIRS) as a new method was proposed for the rapid and nondestructive measurement of citric acids in orange juice. High performance liquid chromatography (HPLC) was used as a reference method for the spectral analysis of citric acids. The original spectral data were preprocessed by the smoothing method with five smoothing points in order to eliminate the noise. Before modeling, large spectral data were compressed by wavelet transform (WT) in Matlab7.01 with the edited program to reduce the dimensions and modeling time, and then the new variables after being compressed were used to build PLS calibration in spectral software Unscrambler 9.5. Considering the effect of different wavelet functions and decomposed scales on the data compressed, the optimal wavelet function Db4 and decomposed scale 5 were determined by predictive residual error sum of squares (PRESS). A total of forty samples were used in our experiment, including thirty samples for the calibration model and ten unknown samples for the prediction. The quality of the calibration model was evaluated by the correlation coefficients (r) and standard error of calibration (SEC), and the prediction results were assessed by correlation coefficients (r) and standard error of prediction (SEP). Comparing WT-PLS model with PLS model, the result of WT-PLS model was r of 0.901 and SEP of 0.937, while the result of PLS model was r of 0.849 and SEP of 1.662, indicating that the prediction result from PLS model with wavelet transform was better than that from PLS model.