M&A prediction literature have been central to the use of financial data over the decades. This has led M&A scholars to call in the contribution of non-financial studies. Accordingly, this study attempted to explore the potential of qualitative data to describe the portrait of target firms’ letters to shareholders and predict the completion of the received M&A offer. The study postulates that analyzing M&A targets’ letters to shareholders could provide relevant categories to describe the attractiveness of firms as M&A targets and predict the completion of the deals. This study employed mixed methods using semi-automated content analysis and decision-tree. The results of the study have provided a portrait description of potential M&A targets and a prediction model comparable to existing literature. Further studies are directed to investigate non-target firms’ letters to shareholders to provide descriptive distinction from target firms’ letters to shareholders, leading to the development of M&A target and non-target classification models. Moreover, the M&A completion prediction model robustness could be further tested on forthcoming M&A announcement. 

• letters to shareholders

• mergers and acquisitions

• prediction

• dictionary building