This paper introduces MIND (Multi-agent Inference for Negotiation Dialogue), a framework for simulating realistic consensus-building among travelers with heterogeneous preferences in travel planning scenarios. Grounded in Theory of Mind (ToM), MIND incorporates a Strategic Appraisal phase that achieves 90.2% accuracy in inferring opponent willingness from linguistic nuances. The framework demonstrates significant improvements over traditional Multi-Agent Debate (MAD) approaches, with a 20.5% improvement in High-w Hit and 30.7% increase in Debate Hit-Rate. Qualitative evaluations using LLM-as-a-Judge confirm superior performance in Rationality (68.8%) and Fluency (72.4%), achieving an overall win rate of 68.3%. This work effectively models human negotiation dynamics through advanced language understanding and multi-agent reasoning.