Phellodendri Chinensis Cortex (PCC) featured with thick cortex and bright-yellow is considered to be of high quality according to traditional appearance traits evaluation mode. However, the correlation between appearance traits and internal quality of PCC has not been scientifically revealed. Here, based on the theory of "Quality Evaluation Through Morphological Identification", the correlation of both sides was studied systematically. Firstly, the thickness of PCC slices was measured by vernier calipers for classification, and the colour of PCC slice was estimated by naked eyes and automatic colorimeter and classified. Secondly, high performance liquid chromatography (HPLC) was used to establish fingerprint chromatogram containing 12 characteristic peaks, and the contents of moisture and ethanolic extractive were determined as well. The correlation among the appearance traits of PCC slice (including the thickness and the spatial values of colour of PCC slice powder: L^*Lightness, a^*Red-Green, b^*Yellow-Blue) and peak areas of 12 characteristic peaks, contents of moisture and extractive were explored through multivariate statistical analysis tools, including Pearson's correlation analysis, principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (PLS-DA) and analysis of variance (ANOVA). Association analysis results showed the morphological parameters (thickness and color) are significantly correlated with 2 kinds of principle chemical constituents (alkaloids and phenolic acids), among them, 5 major constituents including 2 isoquinoline alkaloids and 3 feruloylquinic acids were simultaneously quantitatively analyzed under the same chromatographic condition for establishing a correspondence between appearance traits and content of internal substances, and the sum of the contents of the five components was significantly higher in the thickness ≥ 4 mm (13.15% ± 2.25%) and bright yellow samples (12.14% ± 2.00%) than that in the thickness < 4 mm (10.89% ± 1.41%) and dark yellow samples (10.32% ± 2.41%). The research results confirm that thickness and colour, two main appearance parameters of PCC slice, can be used as the indicators for evaluating the quality PCC slice, which to some extent interprets the scientific connotation of traditional evaluation theory of "thick and yellow are better". At the same time, the results provided substantial data and foundation for the establishment of commodity grade standards of PCC slice.