Single-shot EPI is the most widely used sequence in diffusion tensor imaging. However, severe distortion in single-shot EPI limits its application for higher resolution images. Multi-shot EPI DTI can reduce distortion but results in longer acquisition time especially when a large number of diffusion-encoding directions are used. Here, we propose a model-based reconstruction framework for EPI DTI to estimate diffusion tensors from undersampled EPI sequences, in order to achieve high resolution diffusion imaging in a shorter scan time. The effectiveness of the proposed model-based method to get precise tensor estimation is validated by DTI simulation and in-vivo experiments.