aspg-38-4310-1792223531 20261017075211 American Scientific Publishing Group admin@americaspg.com American Scientific Publishing Group Journal of Sustainable Development and Green Technology JSDGT 2836-5399 2026 6 1 Saad Metawea Professor of Finance, Faculty of Commerce, Mansoura University, Egypt Maha Metawea Associate Professor of Finance, Faculty of Business Administration, Delta University for Science and Technology, Egypt Renewable electricity growth is central to sustainable development, decarbonization, and green-technology planning. However, much of the forecasting literature remains focused on plant-level or narrow-horizon technical prediction, with limited attention to country-level decision support for investment screening, transition monitoring, and strategic benchmarking. This study develops a business analytics framework to forecast the renewable share of electricity generation and classify countries by renewable-transition level using a cross-country panel based on the Our World in Data Energy database. The empirical sample comprises 5,162 country-year observations from 213 countries over the period 2000–2025 and includes measures of electricity demand, electricity generation, primary energy use, greenhouse-gas emissions, and energy-system structure. Three regression models and three classification models were evaluated using a fixed train–test de sign. The random-forest regressor achieved the best continuous forecasting performance, with MAE = 3.536, RMSE = 6.466, and R2 = 0.960, while the random-forest classifier delivered the best tier-classification performance, with 93.998% accuracy and macro-F1 = 0.940. Feature-importance analysis identified greenhouse-gas emissions, energy intensity, electricity generation, electricity demand, and per-capita electricity consumption as the most influential predictors. The findings indicate that renewable-transition benchmarking can be framed as a managerial analytics problem, extending sustainability research beyond descriptive monitoring toward practical decision support for business and policy planning. 2026 09 15 4310 https://creativecommons.org/licenses/by/4.0/ 10.54216/JSDGT.060102 https://americaspg.com/journal/38/article/4310 https://americaspg.com/storage/articles/manuscripts/01M0RA1RMMSCA20H3EGRNWAGRR.pdf