This paper considers the effect of using different probe and gallery sensors on the performance of 3D face recognition. We report results of recognition experiments using face scans of 120 different persons, taken with two different commercial scanners, each at two different times. Our matching algorithm is a version of ICP, which is a popular approach to 3D face recognition. We find substantial differences in recognition rate between the sensors considered in part due to the different types of imaging artifacts produced. When matching data across sensors, the higher-quality data should be the enrollment data.