Many events in the world occur with some quantity that shows a level of the occurrence. This paper discusses reasoning with the normalized level of the occurrence, which we call intensity, and proposes intensity reasoning by constraint propagation based on causal relationships. The knowledge used in the reasoning is given by a directed asyclic graph called causal network. Each node in the network expresses an event with an intensity in [0,1], and each arc between two nodes does a causal relation defined by a function that gives the relation between intensities of those nodes. The reasoning is conducted by constraint propagation to derive a rage of intensity of an arbitrarily chosen node when those of some other nodes are given.