Abstract We present criteria for separately classifying stars and unresolved background galaxies in photometric catalogs generated with the point-spread function fitting photometry software DOLPHOT from images taken of Draco II, WLM, and M92 with the Near Infrared Camera (NIRCam) on JWST. Photometric quality metrics from DOLPHOT in one or two filters can recover a pure sample of stars. Conversely, colors formed between short-wavelength and long-wavelength filters can be used to effectively identify pure samples of galaxies. Our results highlight that the existing DOLPHOT output parameters can be used to reliably classify stars in our NIRCam data without the need to resort to external tools or more complex heuristics.