Verification of Rule Based Systems has largely concentrated on checking the consistency, conciseness and completeness of the rulebase. However, the accuracy of rules vis-à-vis the knowledge that they represent, is not addressed, with the result that a large amount of testing has to be done to validate the system. For any reasonably-sized rulebase it becomes difficult to know the adequacy and completeness of the test-cases. In case a particular test-case is omitted the chances of an inaccurate rule remaining undetected increases. We discuss this issue and define a notion of accuracy of rules. We take the view that a rule represents a concept of the domain and in the scenario of Formal Concept Analysis, works on objects and attribute-value space. We then present a mechanism to measure the level of accuracy using the Rough Set Theory. In this framework, accuracy can be computed as a ratio of the objects definitely selected by the rule (the lower approximation) to the objects possibly selected by the rule (the upper approximation) with respect to the concept that it encodes. Our algorithm and its implementation for PROLOG clauses is discussed.