Miniaturization of the channel size of heat exchanging devices increases the surface to volume ratio, thus promotes higher heat transfer. Operating in two-phase flow further increases the coolant's ability to transfer heat due to the higher latent heat compared to sensible heat in a single phase flow. Many studies have been done to obtain heat transfer coefficient correlations that can accurately predict heat transfer phenomenon. But, there is a factor that influences their accuracy; the effects near the dryout region. Heat transfer has been found to decrease when dryout occurs. Available correlations cannot predict the occurrence of dryout in flow boiling heat transfer. This study analyzed the dryout region between three previous heat transfer coefficient correlations for propane (R290) of a similar form for different values of mass flux and heat flux as the vapour quality changed. It was found that disagreements between predicted and experimental coefficient occurred when the vapour quality is between 0.6 and 0.8. Multiobjective Genetic Algorithm (MOGA) optimization was then utilized to obtain simultaneous maximization of the nucleate boiling and forced convective boiling heat transfer, two mechanisms contributing towards boiling heat transfer and results showed that MOGA is capable of predicting the dryout region under optimized conditions. The optimization works showed that when the mass flux, G is around 200 kgm-2s-2, heat flux, q is around 19 kW m-2, the vapour quality range must be taken into account which is between 0.0 until 0.8 before the dryout occurs. This can be used as guide to controlling heat exchanging devices such that two phase flow boiling occurs as predicted with the maximum heat transfer desired.