This study examines the impact of climate risk-related scores on firm value across seven key global stock markets in the U.S., Europe, Canada, Japan, and China. Utilizing sustainability data from the London Stock Exchange Group's DataStream, we applied machine learning techniques such as Ridge Regression, Lasso Regression, XGBoost, ElasticNet, Random Forest Regressor, and LGBM Regressor. According to our performance criteria, Random Forest regressor outperforms others methods. Our findings reveal that CO2 emissions significantly influence firm value, while other sustainability factors are less impactful. This underscores the importance of standardized ESG datasets and their critical role in determining firm value.