Aberrant serum N‐glycan profiles have been observed in multiple cancers including non‐small‐cell lung cancer (NSCLC), yet the potential of N‐glycans in the early diagnosis of NSCLC remains to be determined. In this study, serum N‐glycan profiles of 275 NSCLC patients and 309 healthy controls were characterized by MALDI‐TOF‐MS. The levels of serum N‐glycans and N‐glycosylation patterns were compared between NSCLC and control groups. In addition, a panel of N‐glycan biomarkers for NSCLC diagnosis was established and validated using machine learning algorithms. As a result, a total of 54 N‐glycan structures were identified in human serum. Compared with healthy controls, 29 serum N‐glycans were increased or decreased in NSCLC patients. N‐glycan abundance in different histological types or clinical stages of NSCLC presented differentiated changes. Furthermore, an optimal biomarker panel of eight N‐glycans was constructed based on logistic regression, with an AUC of 0.86 in the validation set. Notably, this model also showed a desirable capacity in distinguishing early‐stage patients from healthy controls (AUC = 0.88). In conclusion, our work highlights the abnormal N‐glycan profiles in NSCLC and provides supports potential application of N‐glycan biomarker panel in clinical NSCLC detection.