<p>Shifting from fossil energy to renewables has become a necessity for attaining sustainable growth and wind energy may play a critical role in this energy transition. Since top economic contributors employ more energy exacerbating environmental deterioration, this empirical effort gauges how wind energy (WIE) and transportation (TRP) affect the varying levels of ecological footprint (EF). Analyzing this topic is in line with the idea of Sustainable Development Goals (SDGs) since the findings of the study will be critical in the context of climate action (goal 13) and sustainable and affordable green energy (goal 7). This study assesses datasets from the 15 largest economies (2000–2021) via the Methods of Moments Quantile Regression (MM-QR). Robustness checks were conducted using Dynamic Seemingly Unrelated Regression (DSUR), Driscoll-Kraay (DK) regression, Feasible Generalized Least Squares (FGLS), and Continuously Updated Fully Modified (CuP-FM) techniques. The reported findings robust to serial correlation, cross-sectional dependence (CD), endogeneity, and heterogeneity reveal that wind energy is effective in decreasing the EF in each country. However, the impacts of wind energy are found to be heterogeneous. TRP escalates environmental deterioration with more pronounced impacts in nations with rising levels of EF. ICT poses varying impacts on EF; however, most of these impacts were statistically insignificant. The outcomes also show that economic development follows a correct path since boosting development beyond a certain level will eventually reduce the environmental burden. Given these findings, a detailed policy framework is put forward to achieve sustainable development by optimizing the impacts of WIE, TRP, and ICT.</p>