Performance prediction is one of the most important research topics of workflow. To investigate the performance of workflow systems in queuing condition, this paper extends traditional WF-net into WFQN (WF queuing network), by modeling tasks as FIFS (first-in-first-service) queues and the source place as the input of tokens following poisson arrival process. Analytical methods are introduced to evaluate the queue-length, wait-time and completion-duration. The case study (especially the case of airline ticket booking application) shows that WFQN can model real-world workflow-based applications effectively. Through Montecarlo simulations in the case study, we show analytical models are verified by simulative results. We also present a sensitivity analysis technique to identify performance bottle-necks of WFQN. This paper concludes with a comparison with relate work.