The debate on the forecasting ability of non-linear models has a long history, and the Great Recession episode provides us with an interesting opportunity for a reassessment of the forecasting performance of several classes of nonlinear models. We conduct an extensive analysis over a large quarterly database consisting of major macroeconomic variables for a large panel of countries. It turns out that, on average, non-linear models cannot outperform standard linear specifications, even during the Great Recession. However, non-linear models lead to an improvement of the predictive accuracy in almost 40% of cases, and interesting specific patterns emerge among models, variables and countries. These results suggest that this specific episode seems to be characterized by a sequence of shocks with unusual large magnitude, rather than by an increase in the degree of non-linearity of the stochastic processes underlying the main macroeconomic time series.