T cells are at the heart of the immune system's ability to distinguish between self and non-self, playing a critical role in both health and disease. The specificity of the T-cell response is mediated by the T-cell receptor (TCR), a product of the unique V(D)J recombination process, which enables interaction with a wide variety of antigens. Given the sheer scale of potential TCR-epitope interactions – stemming from both the enormous epitope and TCR repertoire diversity -- experimental validation of each TCR interaction is not feasible. This has spurred the development of TCR-epitope prediction models that aim to narrow down the search for immunogenic epitopes, thereby streamlining research and reducing costs. Our webinar will delve into these predictive strategies, highlighting their importance in advancing immunological research and applications. During the webinar we will discuss a range of prediction strategies, including databases, machine learning, and structure-based methods. To improve accessibility and understanding on when to implement a tool, we will use real-life examples to illustrate their practical benefits. Additionally, we will address the challenges and pitfalls associated with these tools, including the complexities of handling negative data in TCR-epitope analysis. Join us as we unlock the potential of TCR-epitope prediction tools and provide you with the knowledge and skills to effectively integrate them into your own research.