LAUSR

Environmental sustainability has emerged as a global imperative, necessitating a nuanced understanding of the determinants of greenhouse gas (GHG) emissions. Although previous studies have highlighted various environmental indicators the specific influence of technological innovation, renewable energy adoption, and forest cover on GHG emissions within G‐7 countries remains insufficiently explored. In this regard, this study examines the impact of these factors on GHG emissions across the G‐7 countries over the period 1995–2021. The empirical results reveal significant cross‐sectional dependence and confirm that technological innovation, renewable energy consumption, and forest conservation significantly contribute to reducing GHG emissions. In contrast, tourism development and economic growth are associated with increased environmental degradation. Moreover, causality analysis uncovers a unidirectional relationship from GHG emissions to technological innovations and from tourism to GHG emissions, alongside a bidirectional causal nexus between renewable energy and GHG emissions. Furthermore, advanced machine learning techniques, including Gradient Boosting (GB) and Extreme Gradient Boosting (XGBoost), identify these variables as key predictors of GHG emissions. These findings underscore the critical role of data‐driven, evidence‐based policymaking in advancing environmental sustainability. By strategically integrating technological advancements and renewable energy frameworks, G‐7 policymakers can more effectively mitigate climate change impacts. The study advocates for comprehensive and targeted policy interventions that address the intricate interplay between economic dynamics and environmental imperatives in the pursuit of a sustainable future.