In the design of wind turbines—onshore or offshore—the prediction of extreme loads associated with a target return period requires statistical extrapolation from available loads data. The data required for such extrapolation are obtained by stochastic time-domain simulation of the inflow turbulence, the incident waves, and the turbine response. Prediction of accurate loads depends on assumptions made in the simulation models employed. While for the wind, inflow turbulence models are relatively well established; for wave input, the current practice is to model irregular (random) waves using a linear wave theory. Such a wave model does not adequately represent waves in shallow waters where most offshore wind turbines are being sited. As an alternative to this less realistic wave model, the present study investigates the use of irregular nonlinear (second-order) waves for estimating loads on an offshore wind turbine with a focus on the fore-aft tower bending moment at the mudline. We use a 5 MW utility-scale wind turbine model for the simulations. Using, first, simpler linear irregular wave modeling assumptions, we establish long-term loads and identify governing environmental conditions (i.e., the wind speed and wave height) that are associated with the 20-year return period load derived using the inverse first-order reliability method. We present the nonlinear irregular wave model next and incorporate it into an integrated wind-wave response simulation analysis program for offshore wind turbines. We compute turbine loads for the governing environmental conditions identified with the linear model and also for an extreme environmental state. We show that computed loads are generally larger with the nonlinear wave modeling assumptions; this establishes the importance of using such refined nonlinear wave models in stochastic simulation of the response of offshore wind turbines.