This study presents a genome-wide prediction and functional analysis of 3D-domain swapped proteins in Brassica oleracea using machine learning and pathway enrichment approaches. By implementing a random forest classifier, along with some novel features and trained on sequence data, we identified approximately 52.4% of B. oleracea sequences as potential candidates for 3D-domain swapping. Functional annotations conducted at the transcript level, focusing on gene ontology (GO) and KEGG pathway enrichment analyses, revealed strong associations with biological processes such as self-pollen rejection, pollen-pistil interaction, and cell recognition, as well as key metabolic pathways like glutathione metabolism, porphyrin metabolism, and flavonoid biosynthesis. This study provides valuable insights into the functional significance of 3D-domain swapping in B. oleracea, establishing a foundation for advanced research and potential applications in plant biology and biotechnology.