Due to the increasing penetration of renewable energy (RE), existing traditional centralized clearing mechanisms are no longer suitable for the local energy market (LEM). Moreover, existing research often overlooks prosumers’ subjective preferences, leading to suboptimal decisions that weaken social welfare and market efficiency. To tackle these challenges, we propose a trading strategy based on prospect theory (PT) and an adaptive learning method to optimize decisions for diverse prosumers and facilitate transactions in LEM. Using blockchain technology, we introduce a smart contract-based matching and settlement mechanism to ensure prosumers’ peer-to-peer (P2P) and efficient transaction process. The advantages of the proposed trading strategy are highlighted through a comparison with the zero intelligence (ZI) method. We also adopted the Remix Ethereum platform to confirm its practicality.