Abstarct: Electricity generation relies on multiple energy sources. In 2023, fossil fuels accounted for approximately 60% of the total power generation in G20 countries, while renewable and other sources comprised the remaining 40%. This study analyzes the optimal composition of electricity generation in G20 nations under the dual constraints of economic growth and greenhouse gas emission reduction, particularly carbon dioxide (CO₂). The core challenge is to identify an energy portfolio structure that simultaneously accommodates these conflicting objectives. To address this issue, advanced econometric models—including static, dynamic, and threshold panel models—have been employed. The threshold panel model captures nonlinear relationships, lag effects, and threshold dynamics between the share of renewable energy, economic growth, and CO₂ emissions. Model parameters have been estimated using R software and research data spanning the period 2000–2023. The findings indicate that increasing the share of renewable energy up to a specific threshold has a significant positive impact on reducing CO₂ emissions without negatively affecting economic growth. However, exceeding this threshold may lead to economic fluctuations and welfare reductions. Consequently, this study provides a novel frxamework for policymakers in G20 countries, enabling them to develop an optimal energy mix baxsed on data-driven insights and nonlinear modeling to ensure sustainable electricity generation.