The European Central Bank has published an occasional paper presenting a Macro-at-Risk framework for assessing risks around baseline ECB and Eurosystem staff projections for euro area inflation and real gross domestic product growth. Models combining indicators from different risk categories consistently outperform single-factor specifications across forecast horizons and evaluation measures, reflecting complementary information rather than simply a larger number of variables. The study finds that predictive value varies by horizon, period and forecasting objective. Labour market indicators are particularly informative for upside inflation risks, while uncertainty, money and credit indicators perform better for downside inflation risks. Financial conditions remain central to growth risk forecasts, with monetary indicators especially useful for downside risks. The framework uses quantile regression models, a dataset of about 350 indicators and the purpose-built M@RX MATLAB toolbox, alongside methods that align model distributions with staff point forecasts and convert quarterly densities into annual distributions. Empirical applications provided timely signals on the direction of subsequent outcomes, including persistent upside inflation risks from late 2022. Because predictive performance is time-varying and state-dependent, the paper recommends regularly reassessing model specifications.