The purpose of the paper is to contribute to the debate on the relevance of nonlinear modeling and forecasts in real exchange rates. Using monthly data from the post¡-Bretton Woods periods for the developed seven countries, we found strong evidence of the presence of nonlinearities in the behavior of real exchange rate, which appeared to be modeled well by an exponential smooth transition autoregressive model. The presence of nonlinear mean¡-reverting adjustment for real exchange rates can be explained by the theoretical models that emphasize the role of transaction and monopolistic pricing. We then used this model to make out¡-of¡-sample forecasting analysis. Overall, we find fairly limited evidence that favors the ESTAR model over a simple random walk benchmark. The nonlinear ESTAR forecasts tend to outperform a simple random walk at longer forecast horizons for UK and Switzerland, but at shorter forecast horizons for Japan and Canada, although the magnitude of the gain from using the ESTAR relative to a random walk is rather small in magnitude at entire forecast horizon.