Code obfuscation is a technique that protects the abstract data contained in a program from malicious reverse engineering and various obfuscation methods have been proposed for obfuscating intention. As the abstract data of control flow about programs is important to clearly understand whole program, many control flow obfuscation transformations have been introduced. Generally, inlining is a compiler optimization which improves the performance of programs by reducing the overhead of calling invocation. In code obfuscation, inlining is used to protect the abstract data of control flow. In this paper, we define new control flow complexity metric based on entropy theory and N-Scope metric, and then apply genetic algorithm to obtain optimal inlining results, based on the defined metric.