This study aimed to distinguish the rhizomes of Paris polyphylla var. yunnanensis (Franch) Hand Mazz (PPY) and Paris veitnamensis (Takht.) H. Li (PV) using metabolomics-based ultra high-performance liquid chromatography coupled with quadrupole time-of-fligh mass spectrometry (UHPLC/Q-TOF MS). First, the UHPLC/Q-TOF MS approach was optimized for metabolite profiling. Then, the MS data were processed using UNIFI™ combined with an in-house library to automatically characterize the metabolites. Based on the exact mass information, the fragmentation characteristics, and the retention time of compounds, and the fragmentation mechanism and retention behavior of steroidal glycosides in the references, the structures identified by UNIFI were further verified. Overall, 146 metabolites, including 42 potential new compounds, were identified or tentatively identified. Pattern recognition analysis of the PPY and PV MS data revealed that they were clearly separated, and 15 potential biomarkers for differentiating between them were selected. These biomarkers were subsequently used to successfully predict the genus of PPY and PV samples. These results indicated that metabolite profiling by UHPLC/Q-TOF MS is an effective, robust approach for determining the characteristic biomarkers that differentiate between TCM species with multiple botanical origins.