Immunotherapy is a futuristic approach that is showing encouraging improvements in the treatment of cancer. It is envisaged that appropriate epigenetic alterations when combined with immune-boosting approaches can synergistically enhance overall patient outcome by addressing concerns such as disease relapse and development of treatment resistance which are caveats in the current standard of care. Essentially, the critical costimulatory and coinhibitory pathways involved in facilitating the immune response are targeted toward fostering patient-specific and disease-specific treatment strategies. Toward this end, cutting-edge molecular biology techniques are shaping novel treatment strategies to enhance immunogenicity and immune susceptibility of cancer cells and boost the anticancer response orchestrated by the immune system. Specifically, several potential biochemicals, genetically engineered immune boosters, and cancer vaccines are under investigation which on successful deployment will uplift immunotherapy as a fundamental strategy that can significantly improve the disease prognosis of cancer patients. All these paradigm shifts in cancer management that are stirred by the biologically inspired immunotherapeutic methods are further reinforced by computational and mathematical model-based approaches by providing a quantitative and qualitative assessment of various aspects of immunotherapy. In this chapter, we present the state of the art of such dynamical models that are used in immunotherapy for cancer and highlight the strengths and weaknesses of the same.