Radiomics is a data-driven imaging science that involves the extraction of quantitative features from medical images, enabling an objective evaluation of tissue characteristics beyond what is perceptible to the human eye. In oral and maxillofacial radiology, radiomics offers a novel approach for the diagnosis of jaw lesions by converting routine imaging data into mathematical descriptors that reflect lesion intensity, shape, texture, and heterogeneity. These features, when analyzed systematically, can serve as radiobiomarkers that aid in differential diagnosis, risk stratification, and prediction of biological behavior. This chapter explores the role of radiomics in identifying and characterizing a wide spectrum of jaw lesions, including odontogenic tumors, cysts, inflammatory conditions, and malignancies. Emphasis is placed on the principles of radiomic feature extraction, the structure of the radiomics workflow, and the integration of artificial intelligence for pattern recognition and decision support. The potential of radiomics to improve diagnostic accuracy, reduce subjectivity, and support personalized treatment planning is highlighted with recent research findings. By framing radiomics as a non-invasive, image-based biomarker tool, this chapter highlights the emerging value of such radiomic features in advancing precision diagnostics in the evaluation of jaw lesions.