The objective of the current work was to evaluate the spectrum-effect relationships between high-performance liquid chromatography fingerprints and analgesic and anti-inflammatory effects of Rubia cordifolia L. extract (RCE), and to identify active components of RCE. Chemical fingerprints of ten batches of RC from various sources were obtained by HPLC, and similarity and hierarchical clustering analyses were carried out. Pharmacodynamic assays were performed in adjuvant-induced arthritis rat model to assess the analgesic and anti-inflammatory properties of RCE. The spectrum-effect relationships between chemical fingerprints and the analgesic and anti-inflammatory effects of RCE were established by gray correlation analysis. UPLC-ESI-MS was used to identify the structures of potential active components, by reference standards comparison. The results showed that a close correlation existed between chemical fingerprints with analgesic and anti-inflammatory activities, and alizarin, 6-hydroxyrubiadin, purpurin and rubiadin might be the active constituents of RCE. In addition, RCE attenuated pathological changes in adjuvant-induced arthritis. The current findings provide a strong basis for combining chemical fingerprints with analgesic and anti-inflammatory activities in assessing the spectrum-effect relationships of RCE.