Laminar-turbulent transition behavior of a wind turbine blade section is investigated in this study by means of field experiments and 3-D computational fluid dynamics (CFD) rotor simulations. The power spectral density (PSD) integrals of the pressure fluctuations obtained from the high-frequency microphones mounted on a blade section are analyzed to detect laminar-turbulent transition locations from the experiments. The atmospheric boundary layer (ABL) velocities and the turbulence intensities (T.I.) measured from the field experiments are used to create several inflow scenarios for the CFD simulations. Results from the natural and the bypass transition models of the in-house CFD EllipSys code are compared with the experiments. It is seen that the bypass transition model results fit well with experiments at the azimuthal positions where the turbine is under wake and high turbulence, while the results from other cases show agreement with the natural transition model. Furthermore, the influence of inflow turbulence, wake of an upstream turbine, and angle of attack (AOA) on the transition behavior is investigated through the field experiments. On the pressure side of the blade section, at high AOA values and wake conditions, variation in the transition location covers up to 44 % of the chord during one revolution, while for the no-wake cases and lower AOA values, variation occurs along a region that covers only 5 % of the chord. The effect of the inflow turbulence on the effective angle of attack as well as its direct effect on transition is observed. Transition locations for the wind tunnel conditions and field experiments are compared together with 2-D and 3-D CFD simulations. In contrast to the suction side, significant difference in the transition locations is observed between wind tunnel and field experiments on the pressure side for the same airfoil geometry. It is seen that the natural and bypass transition models of EllipSys3D can be used for transition prediction of a wind turbine blade section for high-Reynolds-number flows by applying various inflow scenarios separately to cover the whole range of atmospheric occurrences.