There are numerous instruments and an abundance of complex information in the traditional cockpit display-control system, and pilots require a long time to familiarize themselves with the cockpit interface. This can cause accidents when they cope with emergency events, suggesting that it is necessary to evaluate pilot cognitive workload. In order to establish a simplified method to evaluate cognitive workload under a multitask condition. We designed a series of experiments involving different instrument panels and collected electroencephalograms (EEG) from 10 healthy volunteers. The data were classified and analyzed with an approximate entropy (ApEn) signal processing. ApEn increased with increasing experiment difficulty, suggesting that it can be used to evaluate cognitive workload. Our results demonstrate that ApEn can be used as an evaluation criteria of cognitive workload and has good specificity and sensitivity. Moreover, we determined an empirical formula to assess the cognitive workload interval, which can simplify cognitive workload evaluation under multitask conditions.