To solve the problem that the interval rules can not be expressed and reasoned based on evidential networks, a conditional evidential network reasoning and decision method based on interval rules is proposed. The method extends fuzzy rules to interval uncertain rules, which can express the uncertainty and fuzziness simultaneously. Then, the interval uncertain rules are translated to interval conditional belief functions as the parameters of the nodes in evidential networks. The decision conclusion can be drawn by the random distribution of the nodes’power sets, which is obtained by conditional inference and evidential fusion. Finally, the effectiveness of the proposed method is illustrated through the air target situation assessment example.