The purpose of this paper is to investigate whether second language writings at different proficiency levels can be distinguished using automatic indices of linguistic complexity. For this study, 35 linguistic measures in 234 essays selected from the Yonsei English Learner Corpus were analyzed in order to identify the best indicators of L2 writing proficiency among the three categories: text length, lexical complexity, and syntactic complexity. The key to this study is the use of computational tools, the L2 Syntactic Complexity Analyzer and the Lexical Complexity Analyzer, which measure different linguistic features of the target language, and a robust statistical method, discriminant function analysis. Results showed that automatic computational tools indicated different uses of linguistic features across L2 writers’ proficiency levels. Specifically, more proficient writers produced longer texts, used more diverse vocabulary, and showed the ability to write more words per sentence and more complex nominalizations. These findings can offer a window to understanding the linguistic features that distinguish L2 writing proficiency levels and to the possibility of using the new computational tools for analyzing L2 learner corpus data.