A new method of feature selection based on association rules is proposed. Association rules have been used in application such as market analysis to capture relationships among items in large data sets. It is shown that association rules can be adapted to feature selection which are used in image analysis and they can automatically identify the most confident feature. Appropriate texture features are selected with this method to serve image classification and simulative results are discussed.