The use of code metrics allows software developers and project managers to evaluate various features of the software (to be built or already in existence), predict workload, determine software complexity and reliability, and quantify the quality of software systems being developed. Articles written in recent years have proposed various methods for solving this problem. However, there is still no very effective approach to measuring software complexity. This article provides a brief overview of existing software complexity metrics and proposes a new hybrid method for computing software complexity. The proposed hybrid method for evaluating software complexity combines the key features of the Halsted, Maccabe, and SLOC metrics and also allows for a more efficient assessment of complexity.