Ni-basesuperalloys are extensively used in high temperature gas turbine engines and energy industries. Due to the high replacement costs of these components, there are huge economic benefits of repairing these components. Laser direct metal deposition processes (LDMD) based on laser cladding, laser fusion welding, and laser surface melting are some of the processes which are used to repair these high value components. Precise control of these processes is important to achieve the desired microstructure, stress distribution, distortions due to thermal stresses and other important output variables. Modelling of these processes is therefore an extremely important activity for achieving any degree of control/optimisation. However, modelling of these processes is not straight-forward due to meltpool flows dominated by Marangoni and buoyancy driven convection. Detailed CFD models are required for accurate prediction of meltpool geometry. But these models are computationally expensive and require greater expertise. To simplify and speed up the modelling process, many researchers have used the isotropic enhancedthermalconductivityapproach to account for meltpool convection. A recent study on mild steel has highlighted that isotropic enhancedthermalconductivityapproach is not able to accurately predict the meltpool geometry. Based on these findings a new approach namely anisotropicenhancedthermalconductivityapproach has been developed. This paper presents an analysis on the effectiveness of the isotropic and anisotropicenhancedthermalconductivityapproaches for laser melting of Inconel 718 using numerical technique. Experimental meltpool geometry has been compared with modelling results. It has been found that the isotropic enhancedthermalconductivityapproach is not able to accurately predict the meltpool geometry, whereas anisotropicenhancedthermalconductivityapproach gives good agreement with the experimental results.