Argumentation-based negotiation approaches have been proposed to present realistic negotiation contexts. This paper presents a novel Bayesian network based argumentation and decision making framework that allows agents to utilize models of other agents. Our goal is to use Bayesian networks to capture the opponent model through an incremental learning process and use the model to generate more effective arguments to convince the opponent to accept favorable contracts.