The Hybrid Annuity (HAM) has emerged as a flagship financial arrangement in public–private partnership (PPP) infrastructure initiatives, integrating components of the classic Engineering, Procurement, and Construction (EPC) approach with an annuity-based payment framework. As attractive as it may be for creating a better risk-sharing mechanism for public and private sectors alike, HAM is also laden with financial uncertainties that can undermine the feasibility, execution efficiency, and long-term viability of the project. This research aims to establish a formal risk management framework for HAM road projects through stochastic financial modelling to ensure better decision-making and risk reduction measures. The study adopts a quantitative and stochastic modelling methodology to identify, assess and mitigate financial risks in HAM-based road infrastructure. Major financial risks such as cost overruns, uncertainty in inflation rates, delays in funding, risks of annuity payments, and delays in land acquisition are comprehensively examined using Monte Carlo simulations and Bayesian networks. A stochastic risk model is constructed to predict 10-year financial sustainability, including probabilistic Net Present Value (NPV) analysis, scenario-based stress testing, and sensitivity analysis. The model presents a data-centric approach to evaluate the financial risk effect on project feasibility, allowing stakeholders such as government bodies, private investors, and financial institutions to make sound investment decisions. Prioritizing high-impact financial risks via Tornado Chart Analysis and Regression-Based Sensitivity Analysis, the research lays before us a risk-adjusted financial forecasting model that enhances funding strategies, financial resilience, and risk allocation mechanisms in HAM projects. The results of this study will aid in policy making and strategic risk planning in HAM road infrastructure, providing stakeholders with sophisticated risk quantification models and decision-support tools. This systematic approach guarantees the long-term sustainability of road projects, maximizing financial efficacy with minimal uncertainties in project execution.