A damage estimation method for support structure of offshore wind turbine using modal parameters is presented for effective structural health monitoring. Natural frequencies and mode shapes for a support structure with monopile of an offshore wind turbine were calculated considering soil condition and added mass. A neural network was learned based on training patterns generated by the changes of natural frequency and mode shape due to various damages. Natural frequencies and mode shapes for 10 prospective damage cases were input to the trained neural network for damage estimation. The identified damage locations and severities agreed reasonably well with the accurate damages. Multi-damage cases could also be successfully estimated. Enhancement of estimation result using another parameters as input to neural network will be carried out by further study. Proposed method could be applied to other type of support structure of offshore wind turbine for structural health monitoring.