Combined　with　the　free-running　model　tests　of　KVLCC　ship,　the　system　identification　(SI)　based　on　support　vector　machines　(SVM)　is　proposed　for　the　prediction　of　ship　maneuvering　motion.　The　hydrodynamic　derivatives　in　an　Abkowitz　model　are　determined　by　the　Lagrangian　factors　and　the　support　vectors　in　the　SVM　regression　model.　To　obtain　the　optimized　structural　factors　in　SVM,　particle　swarm　optimization　(PSO)　is　incorporated　into　SVM.　To　diminish　the　drift　of　hydrodynamic　derivatives　after　regression,　a　difference　method　is　adopted　to　reconstruct　the　training　samples　before　identification.　The　validity　of　the　difference　method　is　verified　by　correlation　analysis.　Based　on　the　Abkowitz　mathematical　model,　the　simulation　of　ship　maneuvering　motion　is　conducted.　Comparison　between　the　predicted　results　and　the　test　results　demonstrates　the　validity　of　the　proposed　methods　in　this　paper.