https://mail.insyma.org/proceedings/files/original/articles/8. Vietnam_Hien Thi Thu Hoang.pdf Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Proceedings of the International Symposium on Management (INSYMA) (Vol 22, 2025) Proceedings meta_title Machine Learning in Financial Performance Prediction: The Role of ESG Author #1 Hien Thi Thu Hoang Author #2 Trieu Dang Viet Author #3 Trang La Thi Thu Abstract/Description This study explores the application of machine learning techniques to predict corporate Environmental, Social, and Governance (ESG) scores, with a particular focus on identifying the most influential factors derived from company reports. Three predictive models - linear regression, random forests, and gradient boosting - were employed to estimate ESG risk scores. The experimental results demonstrate that the gradient boosting model outperforms the other approaches in predictive accuracy. Analysis using Shapley Additive Explanations (SHAP) reveals that industry classification is the most significant determinant of ESG scores, followed by key financial indicators such as Price/Sales ratio, Price/Book ratio, and Market Capitalization. The proposed predictive framework offers valuable insights for investors and corporations, facilitating informed investment decisions and strategic enhancements in ESG performance. keywords a;b;c;d ESG, Random Forest, Decision Tree, Logistic Regression, financial performance, machine learning publication_date 2025/06/20 2025/06/20 pdf_url https://insyma.org/proceedings/files/articles/8. Vietnam_Hien Thi Thu Hoang.pdf abstract_html_url https://insyma.org/proceedings/items/show/ https://insyma.org/proceedings/items/show/502 firstpage 1171 lastpage 1174 issn 3047-857X 3047-857X conference Proceedings of the International Symposium on Management (INSYMA) Proceedings of the International Symposium on Management (Volume 21, 2024) publisher_name Fakultas Bisnis dan Ekonomika, Universitas Surabaya Fakultas Bisnis dan Ekonomika, Universitas Surabaya no article 190 Volume 22 authors Hien Thi Thu Hoang, Trieu Dang Viet, Trang La Thi Thu Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Machine Learning in Financial Performance Prediction: The Role of ESG Creator An entity primarily responsible for making the resource Hien Thi Thu Hoang