A sustainable supply of electric power is a prerequisite to foster all sorts of development in anyrncountry. Development of electricity infrastructure is undoubtedly a capital intensive project thatrnneeds a careful planning especially when future expansion of Generation and Transmission systemsrnis taken into consideration. To keep Ethiopia abreast with other developing countries, the existingrngap between the electric power demand and supply scenario of the country must be bridged. Tillrnnow, the country is still deeply entrenched in constructing opportunity for development due tornfrequent power outages resulting from an insufficient transmission lines even if there is enoughrngeneration capacity for existing demand. Furthermore, inefficient transmission and distributionrnfacilities have been another recounted setback in the electric power sector of the country. Moreover,rnwithin the ambient of socio economic development and increase in human population, electric loadrndemand will tend to increase from time to time over the year to come. Thus, the performance of thernexisting transmission system facilities must be investigated and appropriate expansion planning mayrnbe carried out to supply the future load demand of the country rnLoad demand forecasting is an essential process in electric power system operation and planning. Itrninvolves the accurate prediction of both magnitude and geographical location of electric load overrnthe different period of the planning horizon. The electric power transmission system has thernprominent role of connecting the generation system with distribution system and large industrialrnconsumers. The design and configuration of transmission network should assure the much neededrnequipoise of electrical load demand and supply for a foreseen future period. rnIn this thesis, long term load forecasting for the whole country is carried out using Artificial NeuralrnNetwork (ANN) and transmission system expansion planning to supply the future load demand ofrnthe country is investigated using highly interactive MATLAB and ETAP 16 software. Thernperformance of the existing transmission system for central and southern regions of the EthiopianrnElectric Power (EEP) is investigated through load flow analysis to identify and find the overloadingrnproblems in the system. A method for choosing the best possible expansion plan for the transmissionrnsystem is presented. Furthermore, contingency analysis (CA) is carried out to investigate thernperformance of the expanded transmission system by simulating the contingencies such as unexpected opening of the power transmission lines, generators tripping condition, sudden changesrnin power generation and unexpected changes in loads. rnThe long term load forecasting used by Ethiopian Electric power (EEP) and EEP master plan (PB)rnengineers for next 26 year was Econometric method while the Artificial Neural Network (ANN)rndoes it for 22 years. Both forecasts have the same load profile. The estimated demand in year ofrn2037 is 137752.09GWh. Comparing the ANN forecast with the earlier EEP master Plane (PB) asrnwell as the updated EEP forecast, total demand is significantly lower, during 2022-2027 period; thernsingle large impact is lower the increased anticipated demand and the export are lower with severalrnbelated anticipations beyond 2030. rnIn the Central and Southern region of EEP, there are twenty nine 132/15kV substations. From this,rn25 (almost 90%) substations are congested and load shading is imminently looming and frequentrnpower interruption is going during peak hours (morning from 09:30 AM- 12PM and night 06:00PM-rn09:00PM.