Biomass-fired boiler plants are being adopted for renewable energy generation due to the combination of environmental benefits and cost effectiveness. The combustion of biomass is highly non-linear and is significantly influenced by the disturbances of the system, especially the moisture content of the wood-chips. High fuel moisture content results in adverse effects on combustion efficiency and stability of the boiler, adversely affecting stability and quality of the generated power and increasing the emission of nitrogen oxides (NOx). The biomass boilers operate in a highly interactive multi-variable environment, and the effects of delays; therefore, conventional control strategies, like proportional-integral-derivative controllers, do not yield satisfactory results for such control problems. This thesis demonstrates the possibilities of stabilizing boiler power and reducing NOx emissions using Model Predictive Control (MPC) for a biomass-fired wood-chip boiler plant with variable moisture content. Using the operational data from the Gävle Energi biomass plant, multi-input single-output (MISO) models for boiler power and NOx emissions were developed using the MATLAB System Identification Toolbox. Two MPC controllers were designed, one for stabilization of boiler power and the second for control of NOx emissions through regulation of the combustion air supply. Simulations showed that using the developed MPC strategy, the stability of the boiler power was maintained and NOx emissions were constrained within acceptable limits, showing that MPC is a viable strategy for control of combustion stability and improvement of biomass-fired boiler systems from an environmental perspective.