Power transformers are key components of electric system networks; their performance inevitably influences the reliability of electricity transmission and distribution systems. To comprehend the thermal ageing of transformers, hot-spot prediction becomes of significance. As the current method to estimate the hot-spot temperature is based on empirical hot-spot factor and is over-simplified, thermal network modelling has been developed due to its well balance between computation speed and approximation details. The application of Computational Fluid Dynamics (CFD) on transformer thermal analysis could investigate detailed and fundamental phenomena of cooling oil flow, and the principle of this PhD thesis is then to develop more accurate and reliable network modelling tools by utilising CFD.In this PhD thesis the empirical equations employed in network model for Nusselt number (Nu), friction coefficient and junction pressure losses (JPL) are calibrated for a wide range of winding dimensions used by power transformer designs from 22 kV to 500 kV, 20 MVA to 500 MVA, by conducting large sets of CFD simulations. The newly calibrated Nu equation predicts a winding temperature increase as the consequence of on average 15% lower Nu values along horizontal oil ducts. The new friction coefficient equation predicts a slightly more uniform oil flow rate distribution across the ducts, and also calculates a higher pressure drop over the entire winding. The new constant values for the JPL equations shows much better match to experimental results than the currently used 'off-the-shelf' constants and also reveals that more oil will tend to flow through the upper half of a pass if at a high inlet oil flow rate.Based on a test winding model in the laboratory, the CFD calibrated network model's calculation results are compared to both CFD and experimental results. It is concluded that the deviation between the oil pressure drop over the pass calculated by the network model and the CFD and the measured values is acceptably low. It proves that network modelling could deliver quick and reliable calculation results of the oil pressure drop over windings and thereby assist to choose capable oil pumps at the thermal design stage. However the flow distribution predicted by network model deviates from the one by CFD; this is particularly obvious for the cases with high flow rates probably due to the entry eddy circulation phenomena observed in CFD. As no experiment validation has been conducted, further investigation is necessary.The CFD calibrated network model is also applied to conduct a set of sensitivity studies on various thermal design parameters as well as loads. Because the studies are on a directed oil cooling winding case, an oil pump model is incorporated. From the studies recommendations are given for optimising thermal design, e.g. narrowed horizontal ducts will reduce average winding and hot-spot temperatures, and narrowed vertical ducts will however increase the temperatures. Doubled oil block washers are found to be able to significantly reduce the disc temperatures, although there is a slight reduction of the total oil flow rate, due to the increase of winding hydraulic impedance. The impact of different loadings, 50%~150% of rated load, upon the forced oil flow rate is limited, relative change below 5%. The correlations between the average winding and hot-spot temperatures versus the load factors follow parabolic trends.