This proof-of-concept study aimed to evaluate the potential of proteomics-based screening, using label-free quantitative proteomic data obtained through SWATH analysis of residual FIT samples, as a triage tool for patients referred for colonoscopy following a positive fecal immunochemical test (FIT). Bioinformatics approaches, including machine learning, were employed to identify potential predictive biomarkers and develop models to distinguish advanced adenomas (AA) and colorectal cancer (CRC) from control samples.