Current research on the retrieval systems for 3D models focuses on using the shape of the models to facilitate search and retrieval. This paper explores the possibility of augmenting the existing 3D shape-based similarity measures by combining shape and color. First, a new descriptor was developed based on the D2 shape descriptor. In our method, N pairs of faces are randomly chosen from a 3D model, with probability proportional to the area of the face. The ratio of the smaller area over the larger area is computed and its frequency stored, generating a frequency distribution of N ratios which is stored as the second dimension of a 2D array, while the first dimension contains the frequency distribution of distances of randomly generated point pairs (the D2 distribution). Second, this research introduces the use of the color features of a 3D model in combination with the shape features to determine similarity. The research involves the study and adoption of an existing 2D color-based similarity measure for 3D models. The analysis of the results is based on the precision and recall of both approaches.