Computers play a serious role in human life, especially web-based applications running twenty four hours per day. These applications are based on relational database management system and they receive many queries from the users. These queries are executed in the commercial systems one by one without any consideration of past experiences and data analysis. The execution of queries can be faster if some rules were derived from the past queries. In this paper, we propose a statistical query-based rule derivation system by the backward elimination algorithm, which analysis the data based on the past queries in order to derive new rules, and then it uses these rules for the execution of new queries. The computational results are presented and analysed that the system is very efficient and promising.