aspg-37-2435-1792223513 20261017075153 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Financial Technology and Innovation FinTechI 2836-5372 2023 3 1 Noura Metawa University of Sharjah, UAE; Faculty of Commerce, Mansoura University, Egypt Saad Metawa Faculty of Commerce, Mansoura University, Egypt In response to the evolving dynamics of corporate responsibility, this research explores the integration of Environmental, Social, and Governance (ESG) factors in sustainable business modeling. The study addresses the pressing need for a strategic framework by delving into the complex interplay between ESG considerations and risk score analysis. Leveraging a comprehensive dataset from S&P500 ESG Scores, our methodology employs the CATBoost algorithm, a categorical boosting technique, for predictive modeling. CATBoost's unique ability to handle categorical variables seamlessly is particularly advantageous for datasets with diverse data types, commonly encountered in ESG analysis. Additionally, we apply SHAP (Shapley additive explanations) methods to shed light on the influential factors shaping our model's predictions, enhancing interpretability. The results, presented through sector-wise ESG analyses, pairwise scatter plots, and distribution analyses, offer a granular understanding of ESG performance across various industries. Furthermore, the SHAP explanation methods provide insights into the relative impact of individual ESG factors on predictive outcomes. The findings not only contribute to the empirical understanding of sustainable business practices within the S&P500 but also offer practical insights for businesses seeking to enhance their ESG integration strategies. 2023 30 37 2435 https://creativecommons.org/licenses/by/4.0/ 10.54216/FinTech-I.030103 https://americaspg.com/journal/37/article/2435 https://americaspg.com/storage/01705767646.pdf