Hypertension is a major global health concern, and there is a need for new antihypertensive agents derived from natural sources. This study aims to identify novel angiotensin I-converting enzyme (ACE) inhibitors from bioactive peptides derived from food sources, particularly highland barley proteins, addressing the gap in effective natural ACE inhibitors. This research employs a machine learning-based pipeline combined with peptidomics to screen for ACE-inhibitory peptides, Gradient Boosted Decision Trees (GBDT) with the best performance among four tested models was used to predict the ACE-inhibitory capacity of peptides derived from papain-hydrolyzed highland barley protein. The selected peptides were validated through computer simulations and in vitro experiments, with FPRPFL identified as the most potent ACE-inhibitor (IC