A decision support model based on machine learning was developed to help choose the best methods for reducing greenhouse gas emissions with renewable energy technologies. By analyzing data from over 1000 emission reduction technologies used in Korea, the model can assess the economic and environmental benefits of these technologies. The goal is to make it easier for users, such as public building managers, to decide which green technologies to adopt for cost savings and environmental protection. The model was validated on a public building in Korea, showing its usefulness in real-world scenarios.