The bibliometric analysis in this study offers an in-depth view of the applications of machine learning (ML) in Business, Management and Accounting, providing insights into growth, trends, and impacts of this disruptive technology over a 15-year span (2010–2025). Drawing from Scopus data, the study analyses the evolution of ML research in Business, Management and Accounting while highlighting key trends such as publications, leading authors, institutions, as well as countries. These data demonstrate a surging rise in ML research after 2015, powered by advances in computing power, the emergence of large-scale datasets, and the discovery of advanced algorithms. The results highlight the international aspect of ML research, with major outputs from the United States, China, and India. Main key research directions include financial forecasting, risk management, and algorithmic trading. Overall, the study sheds light on promising areas of research for both researchers as well as financial analysts and policymakers, showcasing the potential of ML in solving contemporary real-world challenges and charting future research areas.