Immunotherapy has emerged as a transformative treatment for non-small cell lung cancer (NSCLC), yet its clinical benefits remain variable among patients. Early and accurate evaluation of treatment response is critical to guide therapeutic adjustments and improve outcomes. This review synthesizes recent advancements in multimodal imaging techniques-computed tomography (CT), positron emission tomography (PET)/CT, magnetic resonance imaging (MRI), and radiomics-for evaluating and predicting immunotherapy efficacy in NSCLC. We analyze the strengths and limitations of conventional morphological criteria (eg, RECIST, iRECIST) and highlight emerging quantitative biomarkers, including CT texture analysis, metabolic parameters (MTV, TLG), and diffusion-weighted MRI metrics. Notably, radiomics demonstrates promise in decoding tumor heterogeneity, PD-L1 expression, and immune microenvironment features, while immuno-PET probes targeting immune checkpoints offer novel insights into immune activity in vivo. Challenges such as pseudo-progression, nodal immune flare, and discrepancies between imaging responses and pathological responses are critically discussed. By integrating morphological, metabolic, and microenvironmental data, multimodal imaging enhances precision in patient stratification and therapeutic monitoring. Future research should prioritize multicenter, AI-driven radiomics validation and targeted tracer development to optimize NSCLC immunotherapy management. This review provides clinicians and researchers with new directions for utilizing multi-modal imaging techniques in developing personalized treatment strategies.