Thrust loading on wind turbines causes quasi-static loading that ultimately introduces fatigue loading on the turbine. Monitoring these quasi-static loads is relevant for assessing the residual lifetime of the asset. However, installing strain gauges on all assets is practically and economically infeasible; only a subset of turbines, referred to as fleet leaders, are instrumented to this level. Interestingly, these quasi-static loads also result in a temporary inclination or tilt of the tower, which can be picked up by accelerometers or inclinometers installed on the tower or nacelle. This paper proposes using gravity-sensitive tri-axial MEMS accelerometers placed in the nacelle to estimate the inclination and load characteristics of a fleet of turbines. To do this accurately, the MEMS sensor needs to be <em>calibrated</em> to offset installation errors and compensate for the turbines’ permanent inclination. For this purpose, long-term data from the MEMS accelerometer are processed, and the constituting offsets are estimated. After calibration, the quasi-static angles induced by loading can be estimated from the accelerometer. The derived load characteristics can then be used to extrapolate bending moments from fully instrumented fleet-leader turbines to the remainder of the wind farm. The bending moment is then used to assess damage-equivalent moments, and it was found that the accelerometer produces damage estimates similar to those obtained from strain gauges. Thus, the approach enables scalable and cost-effective farmwide load monitoring.