Reactivity controlled compression ignition (RCCI) is an advanced low temperature combustion strategy that utilizes a combination of two fuels to produce a combustion with high thermal efficiency and near zero emissions of NOx and soot. One of the main challenges in implementing RCCI combustion in real engines is efficient control of the combustion process. A model-based control approach has been previously proposed for this task. However, due to the nonlinear nature of the RCCI process, linear control approaches have been restricted around certain operating points. A wider operating range has required the tuning and combining of multiple linear controllers. This thesis aims to solve this issue via the development of a nonlinear model predictive controller (NMPC) capable of working in the entire operating range of the RCCI combustion without excessive tuning. A physics-based RCCI combustion model found in the literature is used as a basis for developing the prediction model used inside the NMPC. The model is validated against an advanced thermokinetic multizone model (UVATZ) developed by University of Vaasa. The developed controller is tested in the MATLAB simulation environment and is shown to be capable of controlling the combustion timing (𝜃50) and the indicated mean effective pressure (IMPE) to follow a given reference by adjusting the fuel blend ratio (BR) and total energy (𝐸 𝑓 𝑢𝑒𝑙). The research of NMPC in the RCCI combustion control is still in its early stages. This thesis provides a solid foundation for developing the controller towards real-world applicability in a flexible-fuel RCCI engine.