Abstract: RNA secondary structure prediction is an important problem in the research field of bioinformatics. Recently, researchers applied metaheuristics to predict RNA secondary structure. In this article, a new predicting method called tabu genetic algorithm based RNA secondary structure prediction (TGARNA) is developed. In the TGARNA algorithm, an improved method for testing the compatibility of stems is given to improve the performance of the population. In addition, tabu search is integrated into genetic operations to prevent inbreeding and maintain a high level of population diversity. Computer simulations show that the proposed approach is effective for predicting RNA secondary structure.