Abstract Reliable forecasts of an economic crisis well in advance of its onset could permit effective preventative measures to mitigate its consequences and become a valuable tool for banking regulation and macroprudential policy. Using the EU14 crisis of 2007–2008 as a template, we develop methodology that can accurately predict a banking crisis several quarters in advance in each country. The data for our predictions are standard, publicly available macroeconomic and market variables that are preprocessed by moving averages and filtering. The prediction models then utilize the filtered data to distinguish pre-crisis from normal quarters through standard statistical classification methodology plus one proposed method, enhanced by an innovative goodness-of-fit measure used in the estimation and in the threshold selection. Empirical results are quite satisfactory and can be used by policy makers, investors and researchers who are interested in estimating the probability of a crisis as much as one and a half years in advance in order to deploy prudential policies. Implications to bank regulatory policy are discussed.