Inflation rate refers to a general rise in prices measured against a standard level of purchasing power. The most well-known measures of inflation are CPI, which measures consumer prices. Box-Jenkins' ARIMA is widely used to predict the economic or financial future outcome. The purpose of this study is to compare the efficiencies of the ARIMA (Autoregressive Integrated Moving Average Model) and Exponential Smoothing for time series CPI forecasting in Bangkok, Northern, Southern, Central, North-Eastern and combined regions. The data under study are of the consumer price index from January 1994 through February 2011, totaling 206 months. The study shows that the RMSE and MAPE have the same result as follows: 1) In forecasting the CPI for the Southern region, it was found that ARIMA performed better than Exponential Smoothing, and 2) In forecasting the CPI for the North-Eastern region and combined regions, Exponential Smoothing performed better than ARIMA.