Herbal medicines have played a vital role in maintaining the health of the world population in the past thousands of years, and have proved to be an effective therapy. It is important to improve our understanding of the effects of the multi-step processing in herbal medicines on the chemical changes to ensure product quality. A proton nuclear paramagnetic resonance ( H NMR)-based evaluation strategy was developed for an efficient process variation exploration and diversified metabolite identification. In this study, 48 process intermediates from 6 commercial batches of the multi-step manufacturing chain of Danshen processing were obtained. Hierarchical classification analysis (HCA) tree based on H NMR spectra clustered the samples according to the processing steps, which indicates that H NMR has the potential capability for critical control point identification based on its adequate information of the organic compounds. Then, principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were applied to distinguish the major metabolite differences between the intermediates before and after the critical control point. In this case, the alkali-isolation and acid-dissolution method was recognized as the most critical process in the multi-step chain of Danshen extract manufacturing. Potential metabolites with the larger amplitude of variation and contributing the most to the discrimination were found to be potential quality markers by -plot, including several previously undetected amino acids. The results in this study are consistent with previous research studies and reference experiments conducted with other analytical tools. Taken together, they prove that H NMR with chemometrics is a very effective process quality control tool to provide comprehensive information on the chemical changes during the processing of herbal medicines, and help with the identification of critical control points and potential critical quality markers.