Rural transit demand forecasting is a tool that aids planners and analysts in the allocation of scarce resources for typically underserved populations. As the number of privately owned automobiles has increased over the past several decades, the provision of public transportation has decreased and lessened the ability of nondrivers to participate in the workforce, take advantage of social service programs, and receive adequate medical care. With Washington State as the case study, three models were developed on the basis of usage characteristics for several existing transportation systems in four Washington counties. Peer analysis was used to create three models with varying levels of complexity and data requirements to predict ridership on countywide public transportation systems. Results indicate that the disaggregated transit demand (DTD) model estimation techniques are the most refined and flexible. The DTD model provides a significant starting point for developing accurate equations for predicting transit need and demand for underserved areas in Washington State.