To address the issues of high communication overhead, unfair node election, and insufficient security in Byzantine Fault Tolerance (BFT)-based consensus algorithms in blockchain systems, this paper proposes a multidimensional reputation score and probabilistic election-based PBFT algorithm, termed MP-PBFT. A node reputation scoring mechanism is designed, evaluating historical behavior, participation level, and honesty, and employing a progressive reward-and-punishment strategy for dynamic scoring. This mechanism allows high-reputation nodes to be adaptively and dynamically selected for key roles, improving consensus efficiency while maintaining security. Furthermore, to overcome centralization tendencies of highest-score selection, a probabilistic election mechanism is introduced for critical nodes. By randomly selecting the advantages of high-reputation nodes and the participation opportunities of low-reputation nodes, honest behavior is encouraged and fairness is improved. Simulation experiments validate MP-PBFT’s performance in communication efficiency, election fairness, and security. Compared to traditional PBFT, MP-PBFT reduces communication overhead by 65% while ensuring fairness and robustness. The proposed approach demonstrates significant advantages in resisting collusive attacks and improving the network’s fault tolerance through the integration of multidimensional reputation scoring and probabilistic elections.