Interpolated Fuzzy Relation Type (IFRT) fuzzy reasoning method has the following two features: (1) the membership function of a reasoning result fuzzy set is not likely to produce a complicated shape, so it is easy to interpret its meaning, (2) if the fuzziness of an input fuzzy set increases, the fuzziness of the reasoning result fuzzy set also increases. Reasoning process of IFRT method is simple in case of given a real number as input. But fuzzy number input case, its reasoning process is not easy as compared with real number input case. This paper shows practical calculus technique of reasoning process for real number input case and fuzzy number input case with concrete example.