We develop distress prediction models for non-financial small and medium enterprises (SMEs) using a dataset from eight European countries over the period 2000-2009. We examine idiosyncratic and systematic covariates and find that macro conditions and bankruptcy codes add predictive power to our models. Moreover, industry effects usually demonstrate significance but provide small improvements. The paper contributes to the literature in several ways. First, using a sample with many micro companies, it offers unique insights into European small businesses. Second, it explores distress in a multi-country setting, allowing for regional and country comparisons. Third, the models can capture changes in overall distress rates and co-movements during economic cycles.

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