The rapid advancement of data analytics has significantly transformed Agricultural Financial Technology (Agri-FinTech) services, creating new opportunities for improving financial inclusion among smallholder farmers. This study conceptually examines the factors influencing the adoption of data-analytics-driven Agri-FinTech services in rural agricultural communities. The paper focuses on identifying technological, individual, and environmental determinants that affect farmers’ willingness to adopt digital financial platforms supported by advanced analytics. The study adopts a conceptual research design based on an extensive review of existing literature related to agricultural finance, financial technology, digital financial services, and technology adoption models such as the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT). The findings indicate that digital literacy, perceived usefulness, trust in digital platforms, infrastructure readiness, and social influence are major determinants influencing the adoption of Agri-FinTech services. Data analytics plays a crucial role in enhancing credit assessment, crop insurance modelling, risk prediction, and farm decision-making through alternative data sources such as satellite imagery, mobile transactions, and weather data. However, adoption remains constrained due to inadequate digital skills, limited connectivity, concerns regarding data privacy, and high technology costs. The study highlights the need for improved rural digital infrastructure, farmer training programs, and transparent data governance policies to promote inclusive and sustainable agricultural financial systems.