Aviation maintenance remains a safety‑critical domain where human‑factor errors persist despite technological progress and regulation. Traditional human‑factors approaches are largely retrospective, offering limited predictive insight when task design, cognitive workload, fatigue, and procedural ambiguity exceed human capacity. This study develops and validates a Human Performance Integration (HPI) Model, a predictive, engineering-oriented framework linking maintenance task design with cognitive constraints and error probability. A mixed‑methods design combines technician interviews (n = 21) and 47 incident reports from a regional airline. Principal Component Analysis (PCA) and Support Vector Machine (SVM) classification models non‑linear interactions among workload, fatigue, task complexity, and documentation clarity. The HPI model functions as a proactive design support tool, enabling engineers to evaluate task structures and workload allocations, embedding human performance limits directly into safety critical design decisions.