It has been demonstrated that triterpenes in Alismatis rhizoma (Zexie in Chinese, ZX) contributed to the lipid-lowering effect on high-fat diet-induced hyperlipidemia. Alisol B 23-acetate, one of the abundant triterpenes in ZX, was used as the marker of quality control for ZX in Chinese Pharmacopoeia, while it could not reflect the lipid-lowering effect because other triterpenes in ZX also had prominent medicinal efficacy. To identify the significantly bioactive triterpenes in ZX, a multiple reaction monitoring (MRM)-based characteristic chemical profile (CCP)-support vector machine (SVM) model was used to explore the relationship between triterpenes and lipid-lowering effect of ZX. Firstly, the content of 87 targeted triterpenes was quantified by the MRM-based CCP using UHPLC-QTRAP-MS/MS. Secondly, the lipid-lowering effect of 30 ZX samples was assessed by 3T3-L1 preadipocytes. Thirdly, 9 of the 87 triterpenes possessing high mean impact value were identified to have significant lipid-lowering effect via the particle swarm-optimized SVM model. The new SVM model constructed by the 9 triterpenes showed good prediction performance and the overall prediction accuracy reached 81.94%. Finally, the real activity of these triterpenes was partly confirmed and was consistent with the prediction of SVM. These results showed that the method for discovery of triterpenes with prominent lipid-lowering activity in ZX was reliable. The proposed method is expected to provide an efficient and rapid approach for screening of active component and drug discovery in traditional herbs.