Visual art works contain a lot of tacit knowledge that is difficult to accurately express in words. If they are expressed quantitatively in a computable form, it helps to apply this part of tacit knowledge to a wider field. Chinese calligraphy style carriers have tacit knowledge of Chinese cultural characteristics, which our research quantitatively interprets. In our study, 33 interpretable features were designed and summarized, and the random forest classification was adopted. As a result, we found that only 8 computational features with concise mathematic form were needed to interpret the differences between the five writing styles of Chinese calligraphy with an accuracy of 66.7 %. Based on these features and the evaluation of five calligraphy styles, we find that some combination of features can cause people’s perception of a particular style and establish the relationship between objective features and people’s subjective feelings. The results can provide inspiration for the creation of artists and designers, and have potential applications in the fields of psychology, design, and human-computer interaction.