To secure surrounding seas of Taiwan, ROC Naval fleet often perform ad-hoc missions which severely endanger the equipment. How to maintain the availability and life of ships effectively with the limited budget become the priority in Navy's continuously task. ROCN endeavors to protect the maritime areas and the equipment often faces harsh operating conditions. Sailing on the sea, it relies on the engine's generating power and its reliability act decisive role as performing combating capability. Nowadays, the maintenance operation based on the producer's documents cannot effectively predict and analyze the time when the ships will break down. Based on the monitoring and historical maintenance record of Vessels in public sector and using Logistic Regression Algorithm, this study construct a predictive model to detect fault of marine engine which can provide a feasible solution for public sector. As a result, the number of equipment malfunctions can be effectively reduced and maintenance costs can be reduced while still increasing the availability in the limited national defense budget.