This paper explores the impact of economic complexity and financial development on energy efficiency through two indicators: energy intensity and carbon intensity, within the top 10 complex economies. Other control variables, such as economic growth, urbanization, and human capital, are also included in the models. Random and fixed-effects estimators with heteroskedasticity-consistent standard errors were used. Clustered random and fixed-effects estimators were considered to handle within-group (cluster) dependence. The study utilized the Driscoll-Kraay (DK) method to address non-spherical disturbances and ensure consistent standard errors and robustness against dependence. Feasible Generalized Least Squares (FGLS) considered entity-specific autocorrelation, and System Generalized Method of Moments (Sys-GMM) accommodated unobserved panel-level effects, were also employed. Our findings reveal that economic complexity is crucial in reducing carbon and energy intensity, highlighting the significance of fostering technological sectors to diversify and sophisticate the productive structure. However, the influence of financial development on these intensity measures remains ambiguous and necessitates further exploration. We propose policy implications aimed at boosting technological sectors, facilitating a green transition in the economy, and advancing the adoption of renewable energy technologies.