To ensure that tidal current turbines are operating at or near design conditions, further detailed investigations are required on turbine performance in real site conditions. Optimising some of the important performance parameters under real site conditions will prove paramount to successful exploitation of this resource at a large scale. In this paper, an optimisation tool is presented which uses a combined Non-dominated Sorting Genetic Algorithm - Blade Element Momentum theory (NSGA-BEM) model. With inputs from XFoil, the design of the turbine blade is optimised by modifying hydrofoil profiles at various blade sections, this process returns new blade profiles by optimising new angles of attack, chord lengths and twist angles at the relevant blade sections. The accuracy of the performance prediction of the BEM solver used in this work is validated against an experimentally validated tidal current turbine blade. The root mean square error of power and thrust coefficient are 0.0182 and 0.0414 respectively when comparing this work with experimental measurements found in the literature. Further work includes implementing computational fluid dynamics, blade loading, cost and biomimetic profiles to form part of the optimisation process, as well as producing prototypes for experimental validation.