Load forecasting is a process of predicting the future load demands. It is important for power system planners and demand controllers in ensuring that there would be enough generation to cope with the increasing demand. Accurate model for load forecasting can lead to a better budget planning, maintenance scheduling, fuel management and to avoid energy wasting and prevent system failure. Therefore, finding an appropriate forecasting model for a specific electricity network is not an easy task. Although many forecasting methods were developed, none can be generalized for all demand patterns. The aim of this paper is to find the appropriate decomposition models for electricity load forecasting of Morocco towards 2030. The multiplicative decomposition with different models of trend is applied to monthly energy data of Moroccan electricity load. The accuracy of these models are calculated and compared. The paper utilizes the coefficient of determination R2 and the mean absolute percentage error (MAPE) as a measure of forecast accuracy. Results show that these time series models can accurately predict the load demand and that the multiplicative decomposition with linear and exponential models slightly outperforms respectively.