We study the real-time Granger-causal relationship between crude oil prices and US GDP growth through a simulated out-of-sample (OOS) forecasting exercise; we also provide strong evidence of in-sample predictability from oil prices to GDP. Comparing our benchmark model "without oil" against alternatives "with oil," we strongly reject the null hypothesis of no OOS predictability from oil prices to GDP via our point forecast comparisons from the mid-1980s through the Great Recession. Further analysis shows that these results may be due to our oil price measures serving as proxies for a recently developed measure of global real economic activity omitted from the alternatives to the benchmark forecasting models in which we only use lags of GDP growth. By way of density forecast OOS comparisons, we find evidence of such oil price predictability for GDP for our full 1970-2009 OOS period. Examination of the density forecasts reveals a massive increase in forecast uncertainty following the 1973 post-Yom Kippur War crude oil price increases.