Efficient tunnel construction planning is essential for minimizing project delays, cost overruns, and safety risks. This study introduces a novel approach using quantitative risk analysis to enhance tunnel construction planning by determining advance steps. Leveraging statistical-probabilistic methods, this approach assesses and quantifies the uncertainties associated with various advance step options. It considers factors such as geological conditions, equipment performance, and operational variables. The methodology aids project managers and engineers in making informed decisions, optimizing advance step selection, and mitigating construction risks. This research showcases its application potential through a case study, illustrating the benefits of data-driven tunnel construction planning for improved project outcomes.