The integration of machine learning into immunopeptidomics data analysis through PSM rescoring holds immense potential. By increasing the number of MS/MS spectra that can be accurately annotated, this approach addresses the important challenge of immunopeptide identification, which can ultimately lead to advances in our understanding of immune responses. While PSM rescoring has gained in popularity over the past few years and has grown into a common analysis strategy, we expect that it will become even more ubiquitous in the near future by shifting from an external post-processing step to a core component integrated in search engines directly.