Abstract： Objective： To explore the prescriptions for treating lung cancer from the perspective of phlegm-toxicity-stasis in the Zhong Liu Fang Ji Da Ci Dian (Dictionary of Tumor Prescriptions)， Zhong Liu Liang Fang Da Quan (Complete Compilation of Good Tumor Prescriptions)，and Zhong Hua Ren Min Gong He Guo Yao Dian (China Pharmacopoiea)，based on the Traditional Chinese Medicine Inheritance Support System (TCMISS，V2.5) and to analyze their medication patterns. Methods：Collect and screen the internal prescriptions for lung cancer of phlegm-toxicity-stasis in the Zhong Liu Fang Ji Da Ci Dian (Dictionary of Tumor Prescriptions)， Zhong Liu Liang Fang Da Quan (Complete Compilation of Good Tumor Prescriptions)，and Zhong Hua Ren Min Gong He Guo Yao Dian (Pharmacopoiea of the People's Republic of China)，enter them into the TCMISS (V2.5) and establish a database. Use data mining methods such as association rules， complex system entropy clustering， and irregular supervised entropy hierarchical clustering to analyze the regularity of the composition and use of TCM prescriptions for lung cancer. Results：A total of 112 prescriptions were ultimately included，involving 281 Chinese medicinals. The four qi were mainly cold，and the five flavors were mainly bitter，mainly attributed to the lung meridian. The top 10 drugs with the highest frequency of occurrence were Oldenlandla Diffusae Herba， Prunellae Spica， Houttuyniae Herba，Coicis Semen，Scutellariae Barbatae Herba，Sargassum，Paridis Rhizoma，Fritillariae Thunbergii Bulbus，Glehniae Radix，and Trichosanthis Fructus. Obtained 10 core combinations and evolved into 5 new ones. Conclusion：TCM prescriptions for treating lung cancer of phlegm-toxicity-stasis，with the main treatment methods of clearing heat，resolving toxin，dissolving phlegm and dissipating masses， and promoting blood circulation and resolving blood stasis. It is appropriately combined with tonifying qi and yin，as well as attacking and supplementing，in order to inhibit the further development of lung cancer and improve its clinical efficacy.