Summary/Abstract
This study addresses the gap in corporate greenhouse gas emissions reporting by developing a machine learning-based model that estimates unreported Scope 1 and Scope 2 emissions. The model combines transparency with high accuracy, allowing for detailed insights into the factors influencing emissions estimates across various sectors and countries. This research is significant for stakeholders needing reliable data for making informed environmental and investment decisions.