Agile Software Development methods have been largely adopted in the last ten years since they have certain advantages over the traditional approaches. However, industrial software development processes are getting more and more complex and dynamic. As a consequence, optimization of software project scheduling has always been big challenges in both practice and academia, even with Agile methods. There is always uncertainty as well as a need for a probabilistic method that better model and predict uncertainty in software projects. This paper proposes Bayesian Networks to model risk factors in Agile software projects as well as managing risks in Agile iteration scheduling. The paper also addresses 19 common risk factors that affect iteration scheduling. Based on the method, a software was developed as a support tool for managers to control their project schedules as it can assess the possibility of each schedule.