Objective To explore the application value of multi-parameter analysis of energy spectrum CT in the pathological classification of lung cancer. Methods The Energy spectrum CT imaging data of 68 patients with lung cancer confirmed by histopathology from May 2017 to May 2018 were retrospectively analyzed, including 20 cases of squamous cell carcinoma, 22 cases of adenocarcinoma, and 6 cases of adenosquamous carcinoma. Energy spectrum CT parameters and energy spectrum curves of the three groups were compared. Results The order was small cell carcinoma group, squamous cell carcinoma group and adenocarcinoma group from more to less as for the effective atomic number and calcium content(P＜0.05). There was no significant difference between the three groups of water base values(P＞0.05). The order was small cell carcinoma group, squamous cell carcinoma group and adenocarcinoma group from more to less as for the iodine value and energy spectrum curve slope(P＜0.05). The slope of the energy spectrum curve had high sensitivity and specificity in identifying squamous cell carcinoma and adenocarcinoma, the AUC value was the largest(0.91). Conclusion Energy spectrum CT can be used as an effective auxiliary method to evaluate the pathological type of lung cancer and improve the clinical diagnosis rate.