Traditional compaction control methods rely primarily on density-based criteria, which are often time-consuming and labor-intensive. This study proposes a deformation-based compaction quality control (QC) method utilizing a smart roller compactor (SRC) equipped with a deformation monitoring system. Field tests were conducted using two different materials with varying gradations, Material A and Material B, to assess the effectiveness of the proposed approach. The results reveal that the rolling deformation value (RDV) generally decreases with the number of compaction passes, and indicate a strong correlation between RDV and dry density for both materials, with coefficients (R²) of 0.9227 and 0.9069, respectively. Additionally, an support vector machine (SVM) model was developed to classify compaction quality based on RDV and compaction meter value (CMV) data, achieving an accuracy rate of 94%. The findings highlight the advantages of real-time monitoring, reduced testing efforts, and improved reliability in assessing compaction quality, offering a promising alternative to traditional density-based methods.