The need for beef in Indonesia tends to increase along with fluctuated beef prices. The existence of price fluctuations will be a risk for producers and consumers. Therefore, price information is necessary, especially the future beef price and price forecasting is the answer to the need. The purpose of this study is to analyze and identify the best forecasting models for domestic and international beef prices. The data used is monthly retail price data for domestic and international beef from 2013:1-2017:12. Four models used in this study, namely decomposition models, ARIMA, moving averages, and Single Exponential Smoothing are applied. The best forecasting method for forecasting domestic and international beef prices is the ARIMA model based on the lowest values of MAD, MAPE, and MSD.