<p>The rapid greenhouse gas emissions have brought about the need to adopt modern sustainable approaches that will enhance productivity and mitigate climate change issues. In the pursuit of carbon neutrality, agroforestry emerges as a powerful ally, intertwining sustainable land use with energy transformation. This study aims to establish the potential of agroforestry to reduce carbon emissions significantly. The study examines the relationships between energy use, agroforestry, economic growth, and carbon dioxide emissions (CO₂) in China using the Autoregressive Distributed Lags and Granger Causality methods. The findings show that in the short run, energy consumption significantly increases CO₂ emissions. Agroforestry and forest area reduce CO₂ emissions. In the long run, the study found that a 1% increase in agroforestry reduces emissions by 0.741. A similar result was found for forest, as a 1% increment resulted in a 5.88% reduction in emissions. On the other hand, a 1% increase in non-renewable energy consumption causes a 0.89% increase in emissions. Economic growth has a positive effect on emissions and affirms the Environmental Kuznets Curve hypothesis. The Granger causality test found that non-renewable energy use, agroforestry, and forest area have a unidirectional causal effect on CO₂ emissions. The study provides critical insights for policymakers to design sustainable policies that address energy and agroforestry needs for sustainable future growth, and cultivate a sustainable and low-carbon future for China.</p>