<![CDATA[Capital budgeting is a crucial aspect of long-term investment decision-making, particularly under conditions of risk and uncertainty. The literature shows that traditional methods such as Net Present Value (NPV) and Internal Rate of Return (IRR) are still dominant, although they are often inadequate to address the dynamics of the global economy, policy, and markets. Therefore, capital budgeting theory and practice are evolving by adopting advanced techniques, including sensitivity analysis, Monte Carlo simulations, decision trees, and real options, which offer flexibility in the face of uncertainty. This study employed a Systematic Literature Review (SLR) method based on the PRISMA 2020 guidelines, with the primary source being the Scopus database. The selection process yielded 2,709 initial articles, which, after filtering for publication year (2020–2025), language, open access, and keyword relevance, were narrowed down to 90 eligible articles for further analysis. Bibliometric data was then mapped using the VOS viewer to visualize the interconnections between topics. The study's results show an increasing publication trend post-COVID-19 pandemic, with research dominated by energy, infrastructure, and climate policy. The analysis also uncovered research gaps, particularly in the digital sector, MSMEs, and developing country contexts. In conclusion, this study emphasizes the need for a hybrid quantitative-behavioral approach to capital budgeting and opens up research opportunities related to the integration of sustainability aspects into investment decisions. Keywords: capital budgeting, risk, uncertainty, bibliometrics]]>
