Building energy modeling is a well-established field but there is a lack of research to support design guidance and energy benchmarking using simulated results. This study presents a methodology for collecting information about planned buildings in Toronto from uploaded building energy modelling files, to be used as a basis of comparison for future models. The methodology includes the development of an algorithm for automating the generation of baseline building models. Key building design and performance characteristics are identified for inclusion in a database of new buildings in Toronto, and a feedback mechanism, to provide design guidance through comparative analysis and program screening, is detailed. The resultant database can be used by individual building design teams, urban planners, or policy-makers, as they work together to reduce the greenhouse gas emissions in Toronto through increased energy efficiency in the built environment.