Rural electrification plays a key role in terms of achieving the target of universal access to electricity by 2030. In order to deploy reliable and sustainable solutions, the sizing phase of decentralized power systems requires specific inputs such as long-term forecasts of the electricity load. In rural contexts, access to electricity is extremely interlinked to social-economic complex dimensions that in turn, influence the electricity demand. In this paper, we rely on System Dynamics for modelling such complexities, and we calibrate the results with data from a hydroelectric-based electrification programme implemented in 2005 in the rural community of Ikondo, Tanzania. We coupled the model with a newly extended version of a load stochastic tool, namely Lifetime – LoadProGen, in order to introduce a more reliable and calibrated approach to long-term electricity load forecasts.