To obtain good relative attributes reduction in decision systems, an algorithm for attributes reduction based on mutual information gain ratio was proposed. Both the value distribution of selected attributes and the mutual information between selected conditional attributes and decision attribute were considered. A new attribute importance measure method was defined from the viewpoint of information theory, and the measure was used as the heuristic information in the proposed algorithm. The most important condition attribute was added to the selected attributes set from empty set. The algorithm was terminated when the mutual information between the selected attributes set and the decision attribute set is equal to that between the whole condition attributes set and the decision attribute set. The experimental results show that the algorithm can effectively reduce the decision system, and that the number of objects after the reduction is small.