• The Journal of the Convergence on Culture Technology
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• v.10 no.6
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• pp.735-740
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• 2024

ESG has become essential considerations for sustainable management. Domestic corporations are preparing response systems for ESG evaluations. Currently, ESG is expressed in ratings, which limits the detailed analysis of its calculations. So, it is necessary to predict and analyze ESG scores. Governance varies with each country's industrial structure, so it is important to consider its specific characteristics. Therefore, we propose a machine learning-based linear regression model to predict ESG-Governance scores for domestic companies. We collect ESG-Governance scores, financial and non-financial variables related to ESG, and preprocess the data. We apply preprocessed data to our machine learning-based linear regression model and validate model performance with 10-fold cross-validation. Our model showed 79.27% accuracy on test sets. We expect that predicting ESG-Governance score based on our model will enhance the ESG evaluation response system for domestic corporate.