Research is reported on a measure of facial similarity in which the similarity of 2 faces is defined as the Euclidean distance between them in a principal-component space. Five studies were conducted in which participants rated sets of facial images, and in which the measure was applied to 2 problems in the eyewitness literature. Comparisons of ratings with distances derived from the principal-component analysis suggest that the measure corresponds reasonably well to perceptions of facial similarity. In addition, the measure correlates strongly with empirical measures of lineup fairness and is related to eyewitness identification performance. Further potential applications include a software tool for constructing arrays of faces of varying similarity, and a software tool for reconstructing facial images from memory.