As construction projects are becoming more deployed and more complicated at the same time, having an instrument for anticipation of success has become a primary requirement for every stakeholder. On this basis, several models have been introduced which implement different methods for anticipation of the entire goals or a series of goals of projects. In this research, at the first step, 16 criteria as instruments of anticipation of success and 33 factors as required instruments for obtaining success were extracted through library studies, semi-structured interviews and the Delphi method. At the next step, by having 169 questionnaires filled by senior managers of construction projects, the importance and priority of each of these 16 criteria and 33 factors for the initial phases of projects were determined according to Iran's local conditions. Ultimately, through modeling of data by a propagation neural network including 35 hidden layers, the anticipator model for success of construction projects during their initial phases was developed with Performance and Regression. This model is able to anticipate the level of realization of projects' success criteria according to the level of realization of success factors at the initial phase.