As unsafe components in herbal medicine (HM), saccharides can a®ect not only the drug appearance and stabilization, but also the drug e±cacy and safety. The present study focuses on the in-line monitoring of batch alcohol precipitation processes for saccharide removal using nearinfrared (NIR) spectroscopy. NIR spectra in the 4000-10,000-cm À1 wavelength range are acquired in situ using a trans°ectance probe. These directly acquired spectra allow characterization of the dynamic variation tendency of saccharides during alcohol precipitation. Calibration models based on partial least squares (PLS) regression have been developed for the three saccharide impurities, namely glucose, fructose, and sucrose. Model errors are estimated as the root-meansquare errors of cross-validation (RMSECVs) of internal validation and root-mean-square errors of prediction (RMSEPs) of external validation. The RMSECV values of glucose, fructose, and sucrose were 1.150, 1.535, and 3.067 mgÁmL À1 , and the RMSEP values were 0.711, 1.547, and 3.740 mg Á mL À1 , respectively. The correlation coe±cients (rÞ between the NIR predictive and the reference measurement values were all above 0.94. Furthermore, NIR predictions based on the constructed models improved our understanding of sugar removal and helped develop a control strategy for alcohol precipitation. The results demonstrate that, as an alternative process analytical technology (PAT) tool for monitoring batch alcohol precipitation processes, NIR spectroscopy is advantageous for both e±cient determination of quality characteristics (fast, in situ, and requiring no toxic reagents) and process stability, and evaluating the repeatability.