A probabilistic wavelet system (PWS) is proposed to model the unknown network fluid dynamical system with stochastic and incomplete traffic data. When compared with the traditional wavelet system, the PWS uses a novel three-domain wavelet function to make a balance among probability, time and frequency domain, which may achieve a robust modeling performance with poor data information. The definition, transformation and implementation of the PWS are presented for the data-based modeling of network system. Simulation studies show that the performance of the proposed PWS is superior to the traditional one in the stochastic and incomplete data-based modeling system.