Agriculture's role in meeting global food needs has historically relied on increased productivity and land expansion. However, conventional agriculture, despite its productivity, poses daunting environmental challenges, including biodiversity loss, climate change, and water pollution. Socio-economic issues such as price instability and rural decline further complicate agricultural sustainability. Agricultural systems face repercussions from challenges they contribute to, such as climate change impacts and soil degradation, raising concerns about resource depletion and public perception of farming practices. While technological advancements such as digitalization offer promise for efficiency improvements, they also introduce potential risks. The United Nations Sustainable Development Goals and the European Union’s Green Deal's Farm to Fork Strategy underscore the necessity of adopting innovative and sustainable agricultural practices. However, achieving agricultural sustainability requires collaborative efforts beyond policy initiatives, involving stakeholders such as farmers, researchers, and civil society organizations. In this regard, context-specific approaches and comprehensive sustainability assessment are crucial for advancing agricultural sustainability and aligning with policy objectives.The primary objective of this thesis is to explore how integrative methodologies can enhance the state-of-the-art of agricultural sustainability assessments. To fulfill this objective, in the first study, a review of agricultural sustainability tools and models was conducted, assessing their thematic coverage of integrative sustainability concepts such as ecosystem services and the UN Sustainable Development Goals (SDGs). In the subsequent study, an interdisciplinary approach integrating policy, law, and foresight analysis was utilized to examine agriculturally related policies and laws, discerning their sustainability implications in the realm of digital agriculture under probable future scenarios. In the last study, stakeholder knowledge was integrated through a participatory modeling approach to construct a Bayesian belief network, which assessed the effects of digital agriculture on agricultural sustainability.The findings of this thesis demonstrate that existing tools and methodologies for assessing agricultural sustainability often lack sufficient integration with the ecosystem service framework and the UN SDGs. Additionally, the thesis emphasizes the advantages of an interdisciplinary approach integrating policy, law, and scenario analysis to evaluate the sustainability impacts of digital agriculture, showing that without clear policy and law to guide and regulate agricultural digitalization, that it will most likely not be leveraged toward achieving sustainability. Finally, the thesis showed that engaging stakeholders in participatory modeling can improve the contextual specificity of agricultural sustainability assessments by capturing both implicit and explicit stakeholder knowledge of local conditions. The thesis demonstrates different analytical tools for managing uncertainty in sustainability assessment. It further highlights that enhancing the comprehensiveness of indicators within sustainability assessment methods will enable better capture of site-specific characteristics of ecosystem service supply and use, while standardization of indicators will help operationalize outcomes for higher levels of sustainability assessment necessary for achieving sustainability goals.