Ece AcarGorkem SariyerSariyer, GorkemAcar, Ece2025-10-06202517453240, 174532321745-32321745-324010.1504/IJIE.2025.1476952-s2.0-105011764638https://www.scopus.com/inward/record.uri?eid=2-s2.0-105011764638&doi=10.1504%2FIJIE.2025.147695&partnerID=40&md5=2cba63eddd6fe50b0019467725e1d688https://gcris.yasar.edu.tr/handle/123456789/8087https://doi.org/10.1504/IJIE.2025.147695The transformative role of machine learning technology in promoting technological innovation leading sustainable growth is becoming increasingly significant in today’s business era. In this study we implemented machine learning technology to classify the companies according to their digital transformation levels. We used manufacturing companies in Borsa Istanbul (BIST) index as the sample. We constructed a digital transformation level index based on text analysis to measure the frequency of keywords related to digital transformation. We used the sampled companies’ financial sustainability corporate governance performance and research & development (R&D) expenditures to model their digitalisation levels. We observed that between the various machine learning algorithms with 82% accuracy Random Forest outperformed the others. We also showed that while R&D expenditure was the most important feature financial performance-related features were also significant. Thus we concluded that companies with higher financial performances especially those making more expenditures for R&D activities have higher digital transformation levels. © 2025 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessClassification, Digital Transformation, Financial Performance, Machine Learning, R&d ExpenditureClassificationMachine LearningR&D ExpenditureDigital TransformationFinancial PerformanceArticle