In the present day scenario, there are large volumes of data available in several fields, which we can make use of effectively, for decision making. This can be achieved by inducing rules through various rule induction approaches that are available. In this paper, we proposed a rule induction algorithm, ELEM, which is an enhanced version of one of the existing rule induction algorithms, LEM1 (3). This is made effective by reducing the database scans required to generate the rules. Also, it provides an incremental approach which makes use of ELEM and deals with any kind of data changes in a dynamic information system. © 2011 IEEE.