Merging galaxies play a key role in galaxy evolution, and progress in our understanding of galaxy evolution is slowed by the difficulty of making accurate galaxy merger identifications. Mergers are typically identified using individual imaging techniques, each of which has its own limitations and biases. With the growing popularity of integral field spectroscopy (IFS), it is now possible to introduce kinematic signatures to improve galaxy merger identifications. I use GADGET-3 N-body/hydrodynamics simulations of merging galaxies coupled with SUNRISE dust radiative transfer simulations to create mockup IFS and images to match the specifications of SDSS-IV’s MaNGA (Mapping Nearby Galaxies at Apache Point) survey. From the mockup galaxies, I have developed the first merging galaxy classification scheme that is based on kinematics and imaging. I describe the imaging portion of the classification scheme, focusing on the results from applying it to a sample of SDSS galaxies.