The VIIRS Ice Surface Temperature (IST) environmental data product provides the surface temperature of sea-ice at VIIRS moderate resolution (750m) during both day and night. To predict the IST, the retrieval algorithm utilizes a split-window approach with Long-wave Infrared (LWIR) channels at 10.76 µm (M15) and 12.01 µm (M16) to correct for atmospheric water vapor. The split-window approach using these LWIR channels is AVHRR and MODIS heritage, where the MODIS formulation has a slightly modified functional form. The algorithm relies on the VIIRS Cloud Mask IP for identifying cloudy and ocean pixels, the VIIRS Ice Concentration IP for identifying ice pixels, and the VIIRS Aerosol Optical Thickness (AOT) IP for excluding pixels with AOT greater than 1.0. In this paper, we will report the pre-launch performance assessment of the IST retrieval. We have taken two separate approaches to perform this assessment, one based on global synthetic data and the other based on proxy data from Terra MODIS. Results of the split-window algorithm have been assessed by comparison either to synthetic "truth" or results of the MODIS retrieval. We will also show that the results of the assessment with proxy data are consistent with those obtained using the global synthetic data.