This research proposes a point forecasting method into Markov switching autoregressive model. In case of two regimes, we proved the probability that h periods later process will be in regime 1 or 2 is given by steady-state probabilities. Then, using the value of h-step-ahead forecast data at time t in each regime and using steady-state probabilities, we present an h-step-ahead point forecast of data. An empirical application of this forecasting technique for U.S. Dollar/ Euro exchange rate showed that Markov switching autoregressive model achieved superior forecasts relative to the random walk with drift. The results of out-of-sample forecast indicate that the fluctuations of U.S. Dollar/ Euro exchange rate from May 2011 to May 2013 will be rising.