Split-sleeve cold expansion technology is a critical process for improving the fatigue life of aerospace structural components. However, the influence of its parameter variations on fatigue performance remains insufficiently studied. This paper systematically investigates the sensitivity of initial hole diameter, thickness of split-sleeve, and diameter of the extrusion zone of the mandrel on the fatigue life of 7050-T7451 aluminum alloy through integrated fatigue testing, finite element simulation, and machine learning methods. Based on the S-N curve model of 7050-T7451 aluminum alloy and the critical distance line method, a fatigue life prediction model for cold-expanded holes was established. The model was then used to generate datasets for training an intelligent fatigue life prediction model. Leveraging 400 000 data points obtained from the intelligent model, Sobol global sensitivity analysis was conducted to quantify the independent and interactive contributions of these parameters to fatigue life. Results indicate that the initial hole diameter has the most significant impact on fatigue life, dominating both independent effects and synergistic interactions, while the influence of Thickness of split-sleeve and mandrel diameter primarily manifests through interactive mechanisms. The study proposes prioritizing tolerance optimization for initial hole diameter while adopting collaborative design strategies for sleeve thickness and diameter of the extrusion zone of the mandrel. This methodology provides an efficient and economical approach for identifying critical process parameters and optimizing designs, demonstrating significant advantages over traditional physical experimentation and finite element analysis..