<p>Blockchain is a groundbreaking innovation that has the potential to reshape digital interactions through decentralization and security. However, most of its security challenges stem from the consensus process and the involvement of potentially untrusted nodes. This survey makes a distinctive contribution by providing a comprehensive review of trust models with a focus on their applicability to blockchain networks. In particular, it examines fuzzy logic–based and multi-criteria decision-making (MCDM)–based computational trust models, comparing their suitability for enhancing blockchain consensus mechanisms. Unlike prior surveys that primarily emphasize consensus algorithms, this work highlights how the integration of computational trust models with consensus can strengthen miner validation, mitigate security risks such as Sybil and 51% attacks, and improve system scalability. Furthermore, we identify existing gaps in the literature and propose future research directions for developing hybrid trust–consensus frameworks. By presenting both a taxonomy of trust models and a roadmap for their integration into blockchain, this paper underlines a novel perspective that enhances the reliability, security, and adoption of blockchain technology.</p>