This article explores the effectiveness of integrating Bayesian Methodology with the Analytic Hierarchy Process (AHP) for Group Decision Making (GDM), focusing on project selection in startups. It emphasizes the importance of careful project selection, aligned with the strategic objectives of the organization. The research employs the Delphi Methodology to gather expert opinions and enhance the reliability of assessments in AHP. The study proposes a consistency adjustment using Bayesian methodology in AHP-GDM, improving the process of reaching consensus on project selection criteria. The results demonstrate the efficacy of the Logarithmic Least Squares Method (LLSM) and the Bayesian approach in resolving inconsistencies, providing a precise and reliable weight distribution for decision criteria. The article contributes to the multicriteria decision-making literature, highlighting the relevance of integrating quantitative and qualitative techniques in project selection, especially in institutional contexts.