Objective To establish a scoring system for patients withnon-small cell lung cancer (NSCLC), complicated by chemotherapy and myelosuppression based on Logistic regression analysis. Methods The clinical data of patients with lung cancer who received chemotherapy in our hospital from January 2018 to April 2024 were collected. The influencing factors of chemotherapy complicated with myelosuppression were analyzed by univariate and Logistic regression, and a nematographic model was established. Results Compared with non-myelosuppressive group, there were statistically significant differences in pre-chemotherapy leukocyte, pre-chemotherapy hemoglobin, ECOG score, use of platinum drugs, use of anti-metabolic drugs, use of anti-microtubule drugs in myelosuppressive group (P<0.05). WBC<4.0×109/L (OR:4.166, 95%CI: 1.521~11.410), hemoglobin<110g/L (OR: 6.926, 95%CI: 1.817~26.392), ECOG score ≥2 points (OR: 2.235, 95%CI: 1.032~4.840), platinum drugs (OR: 5.738, 95%CI: 2.514~13.097), anti-microtubule drugs (OR: 4.284, 95%CI: 1.853~9.905) and anti-metabolic drugs (OR: 7.180, 95%CI: 2.608~19.769) was an independent risk factor for chemotherapy complicated with myelopathic depression in lung cancer patients (P<0.05). Model verification results showed that the C-index was 0.817 (95%CI: 0.783~0.851), the calibration curve of the model was close to the ideal curve, and the AUC of the ROC curve was 0.811 (95%CI: 0.780~0.842), which showed a net benefit of the model within the range of 10% to 87.5%. Conclusion The constructed nomogram model can effectively predict the risk of chemotherapy complicated with myelosuppression in non-small cell lung cancer patients.