Abstract Background Emerging evidence suggests that treatment of NSCLC brain metastases with immune checkpoint inhibitors (ICIs) is associated with response rates similar to those of extracranial disease. Programmed death-ligand 1 (PD-L1) tumor proportion score (TPS) serves as a predictive biomarker for ICI response. However, the predictive value of brain metastasis-specific (intracranial) PD-L1 TPS is not established. We investigated the role of intra- and extracranial PD-L1 TPS in NSCLC patients treated with ICI following brain metastasis resection. Methods Clinical data from NSCLC patients treated with ICI following brain metastasis resection (n = 64) were analyzed. PD-L1 TPS of brain metastases (n = 64) and available matched extracranial tumor tissue (n = 44) were assessed via immunohistochemistry. Statistical analyses included cut point estimation via maximally selected rank statistics, Kaplan–Meier estimates, and multivariable Cox regression analysis for intracranial progression-free survival (icPFS), extracranial progression-free survival (ecPFS), and overall survival (OS). Results PD-L1 expression was found in 54.7% of brain metastases and 68.2% of extracranial tumor tissues, with a median intra- and extracranial PD-L1 TPS of 7.5% (0 – 50%, IQR) and 15.0% (0 – 80%, IQR), respectively. In matched tissue samples, extracranial PD-L1 TPS was significantly higher than intracranial PD-L1 TPS (p = 0.013). Optimal cut points for intracranial and extracranial PD-L1 TPS varied according to outcome parameter assessed. Notably, patients with a high intracranial PD-L1 TPS (> 40%) exhibited significantly longer icPFS as compared to patients with a low intracranial PD-L1 TPS (≤ 40%). The cut point of 40% for intracranial PD-L1 TPS was independently associated with OS, icPFS and ecPFS in multivariable analyses. Conclusion Our study highlights the potential role of intracranial PD-L1 TPS in NSCLC, which could be used to predict ICI response in cases where extracranial tissue is not available for PD-L1 assessment as well as to specifically predict intracranial response.