Chimeric Antigen Receptor (CAR) immunotherapy utilizes genetically-engineered immune cells that express a unique cell surface receptor that combines tumor antigen specificity with immune cell activation. In recent clinical trials, the adoptive transfer of CAR-modified immune cells (including CAR-T and CAR-NK cells) into patients has been remarkably successful in treating multiple refractory blood cancers. To improve safety and efficacy, and expand potential applicability to other cancer types, CARs with different target specificities and sequence modifications are being developed and tested by many laboratories. Despite the overall progress in CAR immunotherapy, conventional tools to design and evaluate the efficacy and safety of CAR immunotherapies can be inaccurate, time-consuming, costly, and labor-intensive. Furthermore, existing tools cannot always determine how responsive individual patients will be to a particular CAR immunotherapy. Recent work in our laboratory suggests that the quality of the immunological synapse (IS) can accurately predict CAR-modified cell efficacy (and toxicity) that can correlate with clinical outcomes. Here we review current efforts to develop a Synapse Predicts Efficacy (SPE) system for easy, rapid and cost-effective evaluation of CAR-modified immune cell immunotherapy. Ultimately, we hypothesize the conceptual basis and clinical application of SPE will serve as an important parameter in evaluating CAR immunotherapy and significantly advance precision cancer immunotherapy. Video abstract Graphic abstract for manuscript CCAS-D-20-00136 by Liu, D., et al., 'The Role of Immunological Synapse in Predicting the Efficacy of Chimeric Antigen Receptor (CAR) Immunotherapy". The various branches of evaluating cancer immunotherapy metaphorically represented as a Rubik's cube. The development of a novel approach to predict the effectiveness of Chimeric Antigen Receptor (CAR)-modified cells by quantifying the quality of CAR IS will introduce a new parameter to the rapidly expanding field of cancer immunotherapy. Currently, no single parameter can predict the clinical outcome or efficacy of a specific type of CAR-modified cell. IS quality will serve as a quantifiable measure to evaluate CAR products and can be used in conjunction with other conventional parameters to form a composite clinical predictor. Much like a Rubik's cube has countless configurations, several methods and combinations of clinical metrics have arisen for evaluating the ability of a given immunotherapeutic strategy to treat cancer. The quality of IS depicting cancer immunotherapy is metaphorically expressed as a Rubik's cube. Each face/color represents one aspect of cancer therapy. Each grid in one face indicates one factor within that aspect of cancer therapy. For example, the green color represents the tumor microenvironment, and one out of the nine grids in the green color indicates suppressor cells (suppressors in green). Changes in one factor may completely alter the entire strategy of cancer therapy. However, the quality of IS (illuminated center red grid) makes the effectiveness of CAR immunotherapy predictable.