When managing the energy performance of a portfolio of buildings over time, climate change can be a threat as it can cause significant changes in energy use patterns. This paper uses artificial intelligence techniques to develop an AI-based forecasting tool, Campus Energy Use Prediction (CEUP) that can help managers to forecast campus future monthly energy use under various climate scenarios. We have leveraged historical energy use data of buildings in the University of Florida, Gainesville, FL to develop CEUP. CEUP was then used to forecast the impact of climate change with the average outdoor temperature of the median, hottest, and coldest years of future climate scenarios of Gainesville, FL as input.