To train the networks, 735 cases from the Severe Hazards Analysis and Verification Experiment (SHAVE) have been analyzed. For each case, nearby radar data has been processed through the MRMS framework. SHAVE hail reports have spacings typically near 2 km and include all hail sizes, including reports of no hail and of non-severe sizes that are typically unavailable from Storm Data. The more complete hail size range and the dense spacing of the SHAVE reports allow for the reports to be gridded and a verification image, rather than just simply a few points, can be generated. Deep, fully-connected neural networks and fully convolutional neural networks will be explored. Network predictions for exact hail size and hail size category will be explored. The results of the networks will be applied to the Multi-Year Reanalysis of Remotely Sensed Storms (MYRORSS), a database of MRMS data that has been completed for the years 1998 through 2011, to develop a hail climatology, which can be compared to previous MRMS-based hail climatologies that primarily only used MESH as the input.