To improve the performance of a case-based reasoning (CBR) classifier, a trustworthiness evaluation method with threshold optimization for case-based reasoning classification is proposed. Firstly, an improved trustworthiness evaluation(TE) strategy is adopted to calculate the trustworthiness value of the suggested solutions achieved in reuse step. Then, the optimal threshold value of the trustworthiness is obtained by using the genetic algorithm(GA). Subsequently, the target case and its suggested solution is divided into the trustworthy set and the untrustworthy set in accordance with this threshold value. Finally, the majority reuse strategy is adopted to adjust the suggested solutions in the untrustworthy set so as to fulfill an overall CBR evaluation classification process. The experimental results show that the proposed method can effectively increase the classification performance and improve the learning ability for a CBR classifier.