Using emotional expressions in a conversation is an efficient way to convey one’s thoughts. Emotional expressions of the persuader have a strong impact to the recipient’s attitude in a negotiation. Studies for a persuasive dialog system, which tries to lead users to the system’s specific goals, show that incorporating users’ emotional factors can enhance the system to persuade users. However, in a human-human negotiation, the persuader can have better outcomes not only through considering the emotion of the other person but also through expressing his or her own emotions. In this paper, we propose an example-based persuasive dialog system with expressive emotion capability. The proposed dialog system is trained by newly collected corpus with statistical learning. Emotional states and the user’s acceptance rate of the persuasion are annotated. Experimental results through crowdsourcing suggested that the system using emotional expressions has a potential to persuade some users who prefer to be used emotional expressions, effectively.