Results indicate that the facial image identification system involving a morphological comparison, an anthropometrical analysis, and an analysis of reciprocal points matching provides accurate and reliable identification. The analysis used the average distance from 16 reciprocal point differences between the 3D and 2D facial images as the matching criterion. Using this technique, the average distance and percentage error at the false positive/false negative (FP/FN) crossover point were 3.1 percent and 4.2 percent, respectively. Two examinees in the study were identified as false positive using the FP/FN crossover point as the threshold. The experimental study involved the 3D facial data of 25 Japanese men whose photographs were obtained using the 3D physiognomic range finder. The 2D left oblique facial images were taken with a digital still camera. In order to evaluate the match of the 3D and 2D facial images of the same individual, the 3D facial image of each participant was compared to the 2D facial image 10 times, for a total of 250 superimpositions. Next, the 3D facial images of 25 participants were compared to the 2D facial images of the other 24 participants, for a total of 600 superimpositions. Sixteen selected points were plotted on the 3D and 2D facial images and then were superimposed on the basis of the subnasale. The average distance from the 16 reciprocal point-to-point differences between both images was used as the matching criterion. In addition to describing the research method and results, the article also offers information on the equipment and operation method of the new computer-assisted facial image identification system, which uses a 3D physiognomic range finder. Tables, figures, references