China is one of the world’s largest countries in potato production and consumption. Cultivar differences have significant effects on the quality and yield of potato products. In order to choose proper potato materials for optimal products’ processing and provide guiding significance for potato processing industry, 8 main quality indicators were tested based on 44 common potato cultivars in domestic. Statistics analysis showed that, there were obvious differences in indicators of different potato cultivars, and the significant correlation was found between most indicators. To reduce the redundancy, principal component analysis (PCA) was used to transform 8 original indicators into 3 irrelevant principal components. The first principal component was represented as the moisture factor. The second principal component was represented as the sugar factor. And the third component was represented as the protein factor. The cumulative percent of 3 principal components reached 75.77% and could effectively reflect the information of the original indicators. Based on PCA scores for 44 potato cultivars, usages of processing or fresh-eating for different cultivars were suggested. Hierarchical clustering with the Ward method was used to divide 44 potato cultivars into 4 categories and the characteristics of each category were analyzed. The result was accordant with PCA scores, and can provide references and uses for different potato cultivars.