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In this study, we refined and validated a method of determining the average refrigeration load in US commercial buildings using a virtual energy audit software called EDIFES. Crucial assumptions made in the analysis were investigated and validated, using variants of the preexisting code. Validation occurred through two methods: a statistics-based population study and a case study. The population study compared a sample of 32 buildings EDIFES analyzed against a group of 129 CBECS buildings based on energy use intensity (EUI). The Wilcoxon rank-sum test was used to determine if there was a statistically significant difference between the two populations. This statistics-based method of validation using the CBECS dataset revealed two key findings. First, it was determined that this analysis of determining refrigeration load should only be performed on food sales buildings. Second, the analysis revealed that the 3 Hour Variant of the refrigeration marker with 60% run time correction factor performed the best, with a p-value of 0.977, meaning there is very little evidence to reject the statement that the two populations have equal medians. The case study approach to validation entailed selecting a food sales building on the campus of CWRU, submetering plug-in refrigeration loads, and using an engineering manual (physics-based analysis) to estimate the load of walk-in units. This analysis demonstrated that, on average, EDIFES effectively captured 94% of the refrigeration load of the building.