Methods: This study established the MFSM method. To demonstrate its effectiveness, we applied this novel approach to analyze Danxi Granules (丹膝颗粒, DXG) and its constituent herbal materials. To begin with, the ultra-performance liquid chromatography (UPLC) was applied to obtain the chromatographic fingerprints of DXG and its constituent herbal materials. Next, the MFSM was leveraged to compress and integrate them into a new fingerprint with fewer analytical units. Then, we characterized the properties and variability of both the original and integrated fingerprints by calculating total quantum statistical moment (TQSM) parameters, information entropy and information amount, along with their relative standard deviation (RSD). Finally, we compared the TQSM parameters, information entropy and information amount, and their RSD between the traditional and novel fingerprints to validate the new analytical method. Results: The chromatographic peaks of DXG and its 12 raw herbal materials were divided and integrated into peak families by the MFSM method. Before integration, the ranges of the peak number, three TQSM parameters, information entropy and information amount for each peak or peak family of UPLC fingerprints of DXG and its 12 raw herbal materials were 95.07 − 209.73, 9390 − 183064 μv·s, 5.928 − 21.33 min, 22.62 − 106.69 min2, 4.230 − 6.539, and 50530 − 974186 μv·s, respectively. After integration, the ranges of these parameters were 10.00 − 88.00, 9390 − 183064 μv·s, 5.951 − 22.02 min, 22.27 − 104.73 min2, 2.223 − 5.277, and 38159 − 807200 μv·s, respectively. Correspondingly, the RSD of all the aforementioned parameters before integration were 2.12% − 9.15%, 6.04% − 49.78%, 1.15% − 23.10%, 3.97% − 25.79%, 1.49% − 19.86%, and 6.64% − 51.20%, respectively. However, after integration, they changed to 0.00%, 6.04% − 49.87%, 1.73% − 23.02%, 3.84% − 26.85%, 1.17% − 16.54%, and 6.40% − 48.59%, respectively. The results demonstrated that in the newly integrated fingerprint, the analytical units of constituent herbal materials, information entropy and information amount were significantly reduced (P < 0.05), while the TQSM parameters remained unchanged (P > 0.05). Additionally, the RSD of the TQSM parameters, information entropy, and information amount didn’t show significant difference before and after integration (P > 0.05), but the RSD of the number and area of the integrated analytical units significantly decreased (P < 0.05). Conclusion The MFSM method could reduce the analytical units of constituent herbal materials while maintain the properties and variability from their original fingerprint. Thus, it could serve as a feasible and reliable tool to reduce difficulties in analyzing multi-components within CMMs and facilitating the evaluation of their quality.