The evaluation of tumor response in Non-Small Cell Lung Cancer (NSCLC) patients undergoing treatment is crucial for assessing prognosis and guiding therapeutic decisions. Traditional RECIST criteria, based on changes in tumor diameter (zD), may not accurately capture tumor response, particularly in cases involving immunotherapy. In this study, we propose an alternative CT RECIST response indicator based on tumor volume change (zV) to reflect pathologic response to neoadjuvant chemo-immunotherapy and prognosis in Non-Small-Cell Lung Cancer (NSCLC) patients. We analyzed 916 tumor lesions using deep learning techniques. By analyzing the relationship between tumor diameter and volume, as well as zD and zV, we observed inconsistencies, especially in cases with irregular tumor morphology, leading to inconsistencies between CT RECIST response by zD. The response measured by zV demonstrated stronger consistency with pathological responses after neoadjuvant therapy. To avoid excessive evaluation in volume-based assessments, an optimal threshold for zV was selected as - 0.6868 rather than RECIST-derived threshold of - 30%. Additionally, zV, but not zD, was statistically significant in relation to overall survival (P-value = 0.0093). Our findings suggest that volume-based response (zV) provides a novel and more precise prognostic indicator than diameter-based methods (zD) for assessing early immunotherapy response in both resectable and advanced NSCLC. AI-driven, volume-based assessment may offer a more reliable alternative for CT RECIST response evaluation, potentially improving personalized cancer care. Future research should focus on refining zV thresholds and improving segmentation accuracy for complex cases to support broader clinical application.