Method names are important for the software development process. It has been shown by some studies that the quality of method names affects software comprehension. In response, some approaches that evaluate comprehensibility of method names have been proposed. However, the effectiveness of existing approaches is limited because they focus on part of names. To deal with the limitation, we propose a novel approach for evaluating comprehensibility of method names and suggesting comprehensible method names using n-gram models. We implemented a prototype tool and conducted two experiments as a case study. Our experiments show that our approach can correctly evaluate 75% method names and successfully suggest 92% actual third words of method names.