Introduction. Inadequate study of the organization of construction in the project documentation is one of the factors that contravene the planned dates for putting objects into operation. Probabilistic graphs make it possible to obtain more justified timeframes for performing individual works, and even the entire project by proceeding a given level of reliability.Methods. The research illustrates the process of building bridges as a complex hierarchical system, functioning in conditions of the initial data stochastic uncertainty. The feature of the proposed integrated approach to the construction organization design is the combination of different methods’ elements of computer-aided design in the MS Project environment. The simulation is based on the generalized network model, calculated on the basis of the matrix (type of work - private work front) by the critical path method. Thus, positive and negative bonds’ stretching in the work interaction as well as organizational breaks could be deterministic, random and probabilistic. The application of the PERT methodology at the stage of preliminary risk assessment in investment projects of bridge construction is substantiated.Results. As a result, the duration of the construction of the real object by calculation in the MS Project was determined under pessimistic, optimistic, normative and expected work duration. The risks’ evaluation of the project implementation in the established time frame was presented. In addition, the example of organizational and technological solutions for bridge crossing by using summer and winter construction seasons was considered.Discussion and conclusions. The algorithm for informational modeling of bridge construction organization is developed. The purpose of such simulation is reliable forecast of construction dates in conditions of statistical uncertainty of time parameters of technological processes. Therefore, the direction of further research would be connected with the justification of the choice of solutions based on the set of acting random factors.