In this paper we introduce a new kind of flow networks, called flow graphs, different to that proposed by Ford and Fulkerson. Flow graphs are meant to be used as a mathematical tool to analysis of information flow in decision algorithms, in contrast to material flow optimization considered in classical flow network analysis. In the proposed approach branches of the flow graph are interpreted as decision rules, while the whole flow graph can be understood as a representation of decision algorithm. The information flow in flow graphs is governed by Bayes’ rule, however, in our case, the rule does not have probabilistic meaning and is entirely deterministic. It describes simply information flow distribution in flow graphs. This property can be used to draw conclusions from data, without referring to its probabilistic structure.