Working fluids are used every day in a plethora of applications ranging from electronics, automotive, aerospace, and many more. With increasing demands for more efficient design and operation in electrical and mechanical components, the criteria for cooling have consequently increased. We are at a point in design optimization where the thermal conductivity of working fluids has become a limiting factor in the design process. Cooling systems are imperative to the functionality of these components which is why it has become a modern challenge to manufacture working fluids with higher thermal conductivities; this is where nanofluids become a major point of interest. A nanofluid is a mixture of nanoparticles within a base fluid. Nanoparticles change the physical properties of the working fluids including the thermal conductivity. This research was focused on expressing the effects of base liquid, temperature, possible surfactant, concentration, and characteristics of nanoparticles including size, shape, and material on thermal conductivity of nanofluids. Several existing theoretical models were developed to predict the nanofluid thermal conductivity. In this research, the level of accuracy of theoretical models was examined with existing experimental data.