This paper delves into the problem of face recognition using color as an important cue in improving the accuracy of recognition. To perform recognition of color images, we use the characteristics of a 3D color tensor to generate a color LDA subspace, which in turn can be used to recognize a new probe image. To test the accuracy of our methodology, we computed the recognition rate across two color face databases. We observe that the use of the LDA color subspace significantly improves recognition accuracy over the standard gray scale approach without sacrificing computational efficiency.