In this study, in order to anticipate the whole sale price for one day old fleshy chicken in Iran, for time horizon of the future one, three and six months, artificial neural network method and Auto Regressive Integrated Moving Average were used. The required data for a period from April, 2001 up to March, 2009 was received monthly by trade union of one day old fleshy chicken producers. Data of a period from April, 2001 up to March, 2009 was used to compare the methods and data of the last six months was used to study the anticipation power. In order to compare the anticipation error of these two methods, Mean Error, Mean Absolute Error, Mean Square Error and Mean Absolute Percent error were utilized. Study results showed that artificial neural network has lower error to anticipate the price for one day old fleshy chicken in time horizons of the future one, three and six months and it is meaningfully more precise than Auto Regressive Integrated Moving Average.