In this paper, we measure the effect of the lighting direction in facial images on the performance of 2 well-known face recognition algorithms, an appearance based method and a facial feature based method. We collect hundreds/thousands of facial images of subjects with a fixed pose and under different lighting conditions through a unique facial acquisition laboratory designed specifically for this purpose. Then we present a methodology for automatically detecting the lighting direction of different face images based on statistics derived from the image. We also detect if there is any glare regions in some lighting directions. Finally we determine the most reliable lighting direction that will lead to a good quality/high performance facial image from both techniques based on our experiments with the acquired data.