SMEs and government share a mutually beneficial relationship that highlights the significant role that public procurement plays in advancing economic development and sustainability. However, this does not rule out the fact that SMEs face significant challenges in obtaining opportunities for public procurement. We aim through this paper to identify various access limits and asses them using Bayesian Networks (BNs). This paper provides a foundation for leveraging BNs’ ability to handle uncertainty and display dynamic data to enhance SMEs’ eligibility and performance in public procurement. The method involves first meta-analysing the corpus of recent research to identify significant risk factors, and then developing a BN model under the guidance of expert knowledge. The calculated Conditional Probability Tables (CPTs) give SMEs a comprehensive understanding of the relationships between risk factors, which promotes proactive management and strategic decision-making. The significance of buyer governance, tender quality, and bidder preparedness in SMEs’ procurement performance is demonstrated by our findings, through our use case. Through this paper, we aim to advocate for more inclusive procurement regulations and tailored assistance programmes to improve SME participation and competitiveness in public procurement.