Objective To analyze and screen the risk factors of both immunohistochemistry and pathology for lung cancer lymphatic metastasis, and to build a mathematical model for preliminary evaluation. Methods By conducting retrospective studies, the information of lung cancer patients in the General Hospital of Air Force from 2009 to 2011 were collected. Both single and multiple unconditional logistic regression analyses were applied to screen total 27 possible factors for lymphatic metastasis. After the factors with statistical significance were selected, the relevant mathematical model was built and then evaluated by means of receiver operating characteristic (ROC) analysis. Results A total of 216 patients were included. The single analyses on 27 possible factors showed significant differences in the following 10 factors: pathological grade (P=0.00), age (P=0.00), tumor types (P=0.01), nm23 (P=0.00), GSTII (P=0.01), TTF1 (P=0.01), MRP (P=0.01), CK14 (P=0.02), CD56 (P=0.02), and EGFR (P=0.03). The multiple factors unconditional logistic regression analyses on those 10 risk factors screened 4 relevant factors as follows: pathological grade (OR=2.34), age (OR=1.02), nm23 (OR=1.66), and EGFR (OR=1.47). Then a mathematical diagnostic model was established based on those 4 identified risk factors, and the result of ROC analysis showed it could improve the diagnostic sensitivity and specificity compared with the single factor mathematical diagnostic model. Conclusion Pathological grade, age, nm23, and EGFR are related with lung cancer lymphatic metastasis, and all of them are the risk factors which have higher adjuvant diagnostic value for lung cancer lymphatic metastasis.