A new method for color appearance matching in an image processing system is proposed in this article. It utilizes categorical color matching for predicting matching colors. Categorical color matching maintains the relative color categorical relationship between the source color and the destination color so that their color names, which are specified by an observer, are identical. The color mapping technique that sets a mapping point by referring to a categorical color matching criterion is defined as categorical color mapping. Categorical color matching provides a mapping pair that has the same color name in both the source color space and the destination color space. Therefore, categorical color mapping has the potential for color appearance matching. Euclidean distance in CIELAB space is normalized color categorically so that color categorical equivalency is established. This article proposes an algorithm for transforming a color categorical normalized distance in the source color space to one in the destination color space. Two CRT monitors with different color temperatures were used in a color appearance matching experiment in a dark room and in ambient light. The performance of categorical color mapping was evaluated by comparing with CIECAM97s and RLAB, which were selected as examples of conventional color appearance models in paired comparison experiments. Categorical color mapping was ranked first in Z-score among all color appearance models both in a dark room and under ambient lighting.