Mechanical ventilation is a life-saving intervention for preterm infants, yet it remains a major risk factor for ventilator-induced lung injury and long-term developmental impairment. In current clinical practice, two different strategies are used: conventional ventilation (CV) delivers pressure- or volume-controlled breaths with tidal volumes exceeding dead space, typically synchronized to spontaneous breathing. High-frequency oscillatory ventilation (HFOV) achieves gas exchange using a constant mean airway pressure and small tidal volumes at high oscillation frequencies without synchronization to patients’ breathing efforts. Despite decades of clinical experience and research, no clear consensus exists on the superiority of either approach. Especially in HFOV, the mechanisms of airflow, regional ventilation, and gas exchange remain only partially understood. Ethical constraints further limit the bedside exploration of novel ventilation strategies, motivating the use of computational approaches. In this contribution, we present our ongoing development of a spatially resolved, physics-based computational model of the preterm lung aimed at investigating ventilation strategies. The central question is whether mechanistic simulations can provide insight into hybrid ventilation approaches that combine favorable characteristics of CV and HFOV while minimizing harmful mechanical loading. The model extends a reduced-order framework of the whole respiratory system to incorporate characteristics of the preterm lung. Lung tissue viscoelasticity is described using a quasi-linear fractional standard linear solid model suitable for the wide dynamic range of mechanical loading encountered under CV and HFOV. Airflow distribution is represented using viscoelastic resistance–inertance elements along the airway tree, with ongoing work on data-driven corrections for transitional and turbulent flow learned from CFD simulations of resolved upper airways. Numerical experiments on a representative preterm lung geometry demonstrate the model’s ability to resolve regional mechanical loading under CV and HFOV, highlighting both current capabilities and remaining challenges toward clinical decision support in neonatal care.