Cancer immunotherapy has brought significant clinical benefits to patients with cancer, including those with lung cancer. Patient-derived tumor xenograft mouse models have become the preferred animal model for translational cancer research and preclinical studies. Given the unmet need for improved predictive models in immuno-oncology, humanized mouse models which are co-engrafted with both human tumors and immune system components have been used to investigate novel immunotherapeutics. These models have similarly been used to predict immune-related adverse events and to develop predictive biomarkers. This review summarizes key concepts related to humanized mouse models. We highlight the various approaches to generate them, factors that are critical to successfully establishing such models, their respective limitations, and considerations in model selection for preclinical lung cancer immuno-oncology research and therapeutic studies.