•A Markov model that tracks and forecasts the potential contagion of bank runs.•Input variables include initial and proportions of cash withdrawals, initial failure rates, and a contagion market factor of bank runs.•Three illustrations of the model along hypothetical banking systems.•Several numerical examples and sensitivity analyses are provided. In this study, we develop a generic Markov model that tracks in real-time and forecasts the potential contagion of bank runs during severe contractionary economic cycles. The proposed model aims to assist regulatory bodies that supervise heterogeneous banking systems by offering an adaptable monitoring scheme. The model calibrates a few input variables including initial cash withdrawals, bank idiosyncratic initial failure rates, allocated proportions of cash withdrawals, and a contagion market factor of bank runs, and it concludes with designated measures for the overall strength of a banking system and for the expected time until a banking system failure, as predefined by policymakers. We also illustrate the functionality of the model along three hypothetical banking systems and further deploy numerical examples and sensitivity analyses, which reveal that initial bank failure rates play a bigger role in the propagation of bank runs than the contagion market factor.