This paper presents an investigation of the optimal estimation of state for Boolean control networks subject to stochastic disturbances. The disturbances are modeled as independently and identically distributed processes that are assumed to be both mutually independent and independent of the current and the historical states. An iterative algorithm is proposed to calculate the conditional probability distribution of the state given the output measurements. This algorithm is applied to the problems of minimum mismatching estimation and maximum posterior estimation of the state. An example is provided to illustrate the proposed results.