This thesis compares maintenance strategies for the Royal Netherlands Navy to optimize cost, man-hours and downtime. A decision support model was developed to evaluate different mixes of Corrective Maintenance (CM), Time-Driven Scheduled Maintenance (TDSM), and Condition-Based Maintenance (CBM) using SAP data and expert input. Results show that CBM application (~20–50%) reduces long-term costs for high-criticality systems, while man-hour efficiency sometimes favors more CM due to underreported labor in existing data. The model supports tailored, data-driven maintenance planning across vessel types and system groups.