This paper describes two methods to construct fuzzy inference rules by the simplified fuzzy reasoning. The present methods have a construction mechanism of the rule unit that is applicable in two parameters: the central value and the width of the membership function in the antecedent part. The first approach is to create a rule unit near the selected rule which has the nearest position from the central input space for the central value. The second is to create a rule unit near the selected rule which has the minimum width for the width. Experimental results are presented in order to show that the proposed methods are effective in difference on the inference error and the number of learning iterations.