Two-dimensional paper networks (2DPNs) hold great potential for transcending the capabilities and performance of today's paper-based analytical devices. Specifically, 2DPNs enable sophisticated multi-step chemical processing sequences for sample pretreatment and analysis at a cost and ease-of-use that make them appropriate for use in settings with low resources. A quantitative understanding of flow in paper networks is essential to realizing the potential of these networks. In this report, we provide a framework for understanding flow in simple 2DPNs using experiments, analytical expressions, and computational simulations.