Following triggered corporate bankruptcies, an increasing number of
prediction models have emerged since 1960s. This study provides a critical analysis
of methodologies and empirical findings of applications of these models across 10
different countries. The study’s empirical exercise finds that predictive accuracies of
different corporate bankruptcy prediction models are, generally, comparable.
Artificially Intelligent Expert System (AIES) models perform marginally better than
statistical and theoretical models. Overall, use of Multiple Discriminant Analysis
(MDA) dominates the research followed by logit models. Study deduces useful
observations and recommendations for future research in this field.