Establishing a regular assistance system for rural low-income populations is essential for advancing rural revitalization and achieving common prosperity. This paper proposes an analytical framework for understanding the governance of low-income issues. Drawing on data from urban and rural household surveys, it examines the size, relativity, and multi-dimensional inequality characterizing the rural low-income population. Based on field research in H City, Province A, the paper further summarizes the current practices and challenges in assisting these populations. It argues that, during the transitional phase, the focus of assistance should shift towards raising income levels, reducing income gaps, and enhancing development capacity and resilience. However, the transition is hampered by several challenges, including inconsistent identification criteria, weak coordination of support measures, and fragmented departmental data systems. In the post-transition period, the core task is to establish a sustainable, data-driven assistance framework. This involves integrating income-based and multidimensional capability-based identification methods to develop stratification standards, while maintaining the dual-track model of "development-oriented assistance" and "social assistance". The rural low-income population can be grouped into three tiers: social assistance recipients, development-oriented support recipients, and resilience-monitoring groups. Correspondingly, the government's governance system must undergo systematic optimization in terms of actors, structures, and accountability mechanisms.