Background: Environmental sustainability is a necessary condition to ensure the long-term viability of agricultural production, as it helps to mitigate the effects of climate change and contributes to the achievement of global goals such as the Paris Agreement (United Nations, 2015a) and the Sustainable Development Goals (United Nations, 2015b). Agricultural production and environmental conditions are closely interrelated, as evidenced by the fact that agrifood system accounts for between 44.1% of global greenhouse gas emissions, in 1990, and 34.6% in 2015 (Díaz-Bonilla, Trigo, & Campos, 2024); meanwhile, climate change generates adverse effects (such as rising temperatures, precipitation variability, and extreme weather events) that impact agricultural productivity and food security (FAO, 2018; Mirzabaev, y otros, 2023). To address these challenges, it is essential to implement sustainable practices (such as sustainable soil management and agroforestry), which benefit carbon sequestration, biodiversity conservation, and productive resilience (Smith & al., 2019; Kuyah, et al.,, 2019). In this regard, transforming the agricultural sector requires financing mechanisms that support such practices. In this context, aligning the banking system toward results-based green lending is a key strategy to facilitate this transition (Díaz-Bonilla, Echevarría, & Vos, 2022). This systematic review aims to assess the environmental impacts of conditional agricultural credit programs across various production systems and regional contexts. By synthesizing findings related to land use, deforestation, soil and water management, and other sustainability outcomes, the review seeks to generate actionable evidence to inform the design and implementation of credit conditional instruments in the agricultural sector. The focus is on understanding whether and how conditionality in credit schemes influences the adoption of sustainable practices and contributes to broader environmental goals. The objective is to synthesize evidence on the environmental outcomes of conditional agricultural credit programs that explicitly include sustainability-related conditions. The review will address the research question: What environmental sustainability outcomes are associated with agricultural credit programs that include conditionalities for sustainable practices among crop or livestock producers? Methods: Literature searches, including grey literature, will be conducted across six bibliographic databases and fourteen organizational websites. Eligibility screening will occur in two stages: (1) title and abstract, and (2) full text. Screening consistency will be evaluated at the title and abstract stage before applying a natural language processing (NLP) model. A subset of 200 records will be screened independently by all team members, and inter-rater agreement will be assessed using Fleiss’ Kappa. Data and key metadata will be summarized in narrative synthesis tables and figures. Where feasible, quantitative effect sizes will be extracted to support meta-analysis. Risk of bias will be assessed for all studies included in the meta-analyses.
