Mineral exploration projects, due to their capital-intensive nature, long development cycles, and reliance on incomplete and uncertain data, are inherently associated with high levels of uncertainty and risk. Decision-making in such projects—particularly in the early stages—without the support of systematic performance evaluation frameworks can lead to resource wastage, cost escalation, and project failure. Accordingly, the present study aims to identify and structure the key performance evaluation indicators for mineral exploration projects and to develop a phase-based conceptual framework tailored to conditions of uncertainty.

In this research, an initial set of indicators was extracted through a systematic review of the scientific literature. Subsequently, the Fuzzy Delphi Method was applied in three consecutive rounds with the participation of 30 experts in the fields of mining and exploration to refine the indicators and achieve consensus. The results of the Fuzzy Delphi analysis indicated that, among the initial indicators, 17 were validated by expert consensus as the final key indicators.

These indicators were then positioned within the three main evaluation study phases—Scoping, Pre-Feasibility Study (PFS), and Feasibility Study (FS)—based on the nature of available information, the level of uncertainty, and the type of managerial decisions required at each stage. The findings demonstrate that a phase-oriented focus on performance evaluation indicators can contribute to the gradual reduction of uncertainty, improvement in decision-making quality, and enhancement of the likelihood of success in mineral exploration projects.

The conceptual framework developed in this study serves as a decision-support tool with practical applicability for project managers, investors, and policymakers in the mining sector. It can also provide a foundation for the development of more advanced performance evaluation and risk management models in exploration projects.