Abstract: A farmland system has been required to balance the food security and ecological sustainability under the dual pressures from global population and global warming. Sustainable human-land relationships can be redefined as the populous large-scale agriculture in China. Among them, the green transition of farmland use (GTFU) is very critical to attain the carbon peaking and neutrality. This research aims to perform on the literature review, thematic analysis and case study, in order to systematically examine the conceptual connotation and research progress on the GTFU. Subsequently, the future outlooks were also proposed to advance the research direction in this field. The mainstream conceptualization of the GTFU was integrated with the "farmland green use" (on the sustainable states/practices like green technologies) and "farmland use transition" (value-neutral morphological variations). Specifically, there was the dynamic shift from the "high-input, high-consumption, and high-pollution " to the "low-consumption, low-emission, high-efficiency" mode. The dominant (quantity, and spatial structure) and recessive (quality, function, and input-output) morphologies were optimized and then driven by policy, markets, and technology—with the core dimensions of the "greenness" (resource-environment-ecology synergy via technology substitution, and resource optimization) and "transition" (fundamental functional shift towards production-ecology integration). The research progress revealed that: 1a) Existing conceptual operationalization of the GTFU was relied on the approaches, like the input-output efficiency (e.g., green eco-efficiency), dominant-recessive morphology transition, social-ecological system attributes (e.g., adaptability, vitality, and resilience), and resource element nexus (e.g., WEF-Carbon). Yet, these approaches were typically overemphasized on the economic efficiency without considering the social/ecological/cultural dimensions or data/complexity constraints. 1b) Spatiotemporal analysis indicated that the overall transition level was moderate-low but rising unevenly, with the significantly regional disparities (e.g., higher levels in the plains/low hills vs. mountains) and the emerging positive spatial autocorrelation. Most studies were confined to the macro-scales with the static snapshots. It was still lacking on the micro-scale granularity and dynamic monitoring. 2a) Influencing factors were the external drivers—natural conditions (terrain, climate, and increasingly extreme weather), socio-economic forces (urbanization showing dual effects: positive via technology adoption/green demand but negative via labor shortage/pollution; economic level generally positive but potentially incentivizing short-term pollution), technology advancement, and policy instruments (crucial yet complex, where excessive intervention was hindered the innovation)—and internal drivers that linked to the stakeholder characteristics (farmers' age/education; and cooperatives/enterprises' scale/capacity). There was also the high spatial heterogeneity. Yet it was still lacking to integrate the frameworks and dynamic simulations (e.g., system dynamics) with the nonlinear interactions across diverse regions. 3a) Multidimensional factors included the ecological gains (pollution/carbon reduction, and soil health/carbon sequestration enhancement), economic benefits (improved efficiency, and productivity, income), and social improvements (employment optimization, and health risk reduction), though the assessment was remained on the fragmented without the "ecological-economic-social" framework or the inter-effect synergies/trade-offs. 3b) Governance policy was progressively evolved from the conceptualization (pre-2015) to the implementation (2015-2017), comprehensive integration (2018-2020), and refined, regionalized, low-carbon strategies (2021-present). The basic quantity protection of the "quantity-quality-ecology" was shifted from the administrative to the tech/institution-integrated approaches. The pathways were still lacked on the regional differentiation and quantitative evaluation. The critical research gaps were then focused on the theoretical foundations, limited characterization, dynamic monitoring, insufficient understanding of nonlinear driver interactions across geographies, fragmented assessment, and inadequate regionally-tailored governance design/evaluation. Therefore, the future research on the GTFU should: 1) develop the interdisciplinary theoretical frameworks that centered on the farmland-relevant social-environmental coupling; 2) enhance the conceptual operationalization with the ecological-economic-social metrics. Big data/AI was used for the standardized and multi-scale dynamic analysis; 3) deepen driver analysis using system dynamics/agent-based modeling to simulate the interactions and scenarios; 4) establish the comprehensive multi-dimensional evaluation on the synergies/trade-offs; and 5) design/evaluate to tailor the "place-based, multidimensional, and multi-level" governance policies via natural experiments and multi-objective optimization. These advancements can greatly contribute to the GTFU theory and practice. Ultimately, the finding can also provide the strong support to the national food security, ecological conservation, carbon goals, and rural revitalization in China.