For the past fifty years, there has been a constant increase in the pressure ratio of gas turbines motivated by the need to increase the cycle efficiency. This has moved the operating pressure of gas turbine combustor to be above the critical pressure of jet fuels. This increasing trend in pressure of combustor, places the next generation gas turbines in supercritical regime of majority of jet fuels, making Supercritical Combustion a significant topic of research in the field of gas turbine. Understanding the fluid behavior at and above the critical point provides opportunity for better and efficient combustor design. The complexity in numerical modelling of supercritical fluids, due to the dramatic property variations, solubility in gas and difficulty in tracking the vanishing interface, requires alternate modelling techniques that are well suited for treating multi-phase systems efficiently. Lattice Boltzmann Methods(LBM) is one such system gaining popularity in the recent decade due to the inherent capability to model complex multi-phase flows. LBM is a hybrid particle-continuum method based on the kinetic theory, which entails solution of the Boltzmann equation for the distribution function of particles properties on a lattice node. Despite the advantages of LBM, there is considerable gap in effective application of this method as a solution for engineering problems. This research work is aimed to address this issue by creating a single and multi-component solver using LBM and making quantitative comparison with commercial fluid dynamic flow solver, ANSYS FLUENT. The results form created single-phase LBM solver agrees with the results from FLUENT single-phase solution in addition to showing superiority in terms of computational time and resources. In case of the multi-component model, LBM provided accurate results with coarser mesh refinement. A detailed investigation of LBM application for two simple systems has been studied and reported,bthus laying a foundation for future numerical investigation of supercritical fluid modelling.