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Simple Summary: Lung cancer is one of the most common cancers and can be difficult to treat. One of the treatment methods uses drugs that target a protein called the epidermal growth factor receptor, but the results vary from patient to patient. In this research, we used a technique called radiomics, which involves analyzing detailed scans of the patients' tumors, to see if we can predict who will respond best to these drugs. We reviewed previous studies and found that this method was promising, with patients showing certain patterns on their scans more likely to have longer periods without disease progression. However, more research is needed to confirm these findings and develop reliable methods of using these scans in clinical practice. In the context of non-small cell lung cancer (NSCLC) patients treated with EGFR tyrosine kinase inhibitors (TKIs), this research evaluated the prognostic value of CT-based radiomics. A comprehensive systematic review and meta-analysis of studies up to April 2023, which included 3111 patients, was conducted. We utilized the Quality in Prognosis Studies (QUIPS) tool and radiomics quality scoring (RQS) system to assess the quality of the included studies. Our analysis revealed a pooled hazard ratio for progression-free survival of 2.80 (95% confidence interval: 1.87–4.19), suggesting that patients with certain radiomics features had a significantly higher risk of disease progression. Additionally, we calculated the pooled Harrell's concordance index and area under the curve (AUC) values of 0.71 and 0.73, respectively, indicating good predictive performance of radiomics. Despite these promising results, further studies with consistent and robust protocols are needed to confirm the prognostic role of radiomics in NSCLC. [ABSTRACT FROM AUTHOR]