Energy, which is a fundamental resource for the universe and one of the indispensable requirements of today’s modern world, plays an important role in many fields. In contrast to traditional energy sources, the utilization of renewable energy sources that offer a sustainable, clean, environmentally-friendly future is growing rapidly. Wind energy, as one of these sources, has become widespread and a focal point for energy production. This study conducted a bibliometric analysis, a data mining technique, on English publications (articles, reviews, proceedings, and book chapters) indexed in SCI-E, SSCI, and ESCI in Web of Science from 2010 to 2023. The analysis examined publication numbers, citations, authors, institutions, countries, journals, publishers, research areas, and keywords, and investigated their connections. To visualize trends, clusters, spatial distribution, and common interactions, Vosviewer, ArcGIS, and Excel were used. Temporal changes were assessed by dividing the years into three periods, showing an increasing trend in publications and citations in recent years. To forecast future changes, a Nonlinear Autoregressive Exogenous time series method predicted the number of future publications and citations. The analysis predicts continued growth in publications and citations until 2030, with a focus on energy fuels research. Finally, a multidisciplinary assessment was conducted to provide a broad perspective on wind energy and contribute to the versatility of the study. The study aims to be a comprehensive resource and guide for researchers working on wind energy and bibliometric analysis.