The primary purpose of this research is to understand those elements that define heavy metals contamination and to propose a novel assessment method based on principal component analysis (PCA) in the Yangping River region of Lingbao City, China. This paper makes detailed calculations regarding such factors the single-factor assessment (Pi) and Nemerowâs multi-factor index (PN) of heavy metals found in the surface water of the Yangping River. The maximum values of Pi (Cd) and Pi (Pb) were determined to be 892.000 and 113.800 respectively. The maximum value of PN was calculated to be 639.836. The results of Pearsonâs correlation analysis, hierarchical cluster analysis, and PCA indicated heavy metal groupings as follows: Cu, Pb, Zn and As, Hg, Cd. The PCA-based pollution index (Pαn) of samplings was subsequently calculated. The relative coefficient square was valued at 0.996 between Pαn and PN, which indicated that Pαn is able to serve as a new heavy metal pollution index; not only this index able to eliminate the influence of the maximum value of Pi, but further, this index contains the principal component elements needed to evaluate heavy metal pollution levels. Keywords: Heavy metals contamination, Hierarchical cluster analysis (HCA), Pollution evaluation, Principal component analysis (PCA), Yangping River