Title: Mapping the knowledge domain of corporate financial distress prediction

Authors: Gurmeet Singh; Ravi Singla

Addresses: Chitkara Business School, Chitkara University, Punjab, India ' University School of Applied Management, Punjabi University, Patiala, India

Abstract: This study attempts to identify current dynamics, prominent contributors, and notable trends in the field of corporate financial distress prediction and to suggest future research possibilities. After final selection, 175 research articles, published between 1985 and July 2023, were used from Scopus database for the current research. According to the findings, corporate financial distress prediction has experienced rapid expansion in the recent years, particularly from 2009 onward. The analysis reveals that Asia (45.32%) and Europe (30.22%) continents account for the majority of research publications. Content analysis reveals the range of research areas that fall under the umbrella of corporate financial distress prediction. These include developing models to predict bankruptcy, applying and re-estimating developed models by including new variables, evaluating the sensitivity and stability of financial ratios and models, contrasting various models and variables, and examining the nature of distress risk and how it relates to stock returns. The current study will be useful for potential researchers who want to study in the field of financial distress or bankruptcy prediction. The study suggests untapped research topics in the field that might be the subject of future studies.

Keywords: bankruptcy prediction; bankruptcy prediction models; bibliometric analysis; content analysis; corporate failure; default risk; financial distress; financial distress prediction; VOSviewer.

DOI: 10.1504/GBER.2026.150348

Global Business and Economics Review, 2026 Vol.34 No.1, pp.1 - 29

Received: 07 Oct 2023
Accepted: 28 Jan 2024

Published online: 10 Dec 2025 *

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