Impact Assessment (IA) is a forward-looking instrument that seeks to proactively advise decision-makers on the potential advantages and disadvantages of a proposed action. IA is an important tool for improving governance in a regulatory framework, and governance promotes the IA process. Furthermore, one must consider governance of IA in relation to how decisions are made by public and private organizations. Governance is at the heart of decision-making. It is about how decisions are made and encompasses more than the need to exhibit transparency, efficiency, and public participation in decision-making. Governance determines also if and when there are opportunities for proponents, regulatory authorities and the public to interact in a balanced and respectful way. Broadly speaking, governance covers the way problems are tackled and opportunities created: it is about how, not what or why. Governance addresses crosscutting issues like the choice of institutions, instruments and processes, as well as decisions about the roles of those who will be aff ected. There is no pre-set governance approach for any particular problem: every case must be tailored to the statutory framework in which it occurs. Some political-administrative traditions tend towards a legislative approach, while others favor efficiency as the key driver; still others believe in a consensual approach. These three approaches represent the three main styles of governance: hierarchical, market-driven, and network-oriented; these usually occur in various combinations. Governance of IA is about managing the IA process, including who has responsibility for what, what are linkages and collaborative approaches; the choice of assessment methods and models (including their assumptions); and who to involve and in which ways. At the same time, IA is part of the overall governance approach because it is a formalized procedure to make decision-making more knowledge-driven and, often, to encourage a role for public comment and substantive participation in decision-making. Success or failure of IA depends to a large extent on its compatibility with the dominant governance style of the decision-makers.