Abstract
This study uses machine learning to predict whether digital intangibles investment enhances financial resilience among UK small- and medium-sized enterprises (SMEs). Using a panel dataset over a fifteen-year period, we compare econometrics and machine-learning algorithm approaches to predicting SME financial resilience and distress risk using insights drawn from the Resource-Based View (RBV) and Dynamic Capability theory. Our findings enrich the SME resilience literature by providing a longitudinal, accounting-based measure of resilience derived from AI-driven forecasting models with superior predictive accuracy in comparison to conventional financial-ratio models. This research deepens understanding of how digital investment shapes long-term financial stability in SMEs and offers practical implications for managers and policymakers driving digital transformation.