The weight of antecedent attributes can't work accurately in the linear combinational belief rule based system usually. Simultaneously, with an increase in the number of evaluation ranks, the new weight activation formula will have negative effects on results. Aiming at the above drawbacks, this paper proposes a two-value and multi-base reasoning method based on the existing belief rule based inference classification algorithm to improve the belief rule based decision system. The evaluation of belief rules in the conclusion are divided into two ranks firstly, which means making a two-value judgment on a decision problem. Then many belief rule bases are set to solve some sub problems simultaneously. Finally results of many sub problems by multi-base reasoning method are mixed to solve the classification problem. Experimental results show the feasibility and effectiveness of the proposed belief rule base reasoning classfication method.