Cone beam computed tomography (CBCT) is widely used in dentomaxillofacial radiology, but it is prone to artifacts due to discrepancies between mathematical modeling and the actual imaging process. Artifacts can interfere with diagnosis and are often mistaken for real structures. This review discusses the most common artifacts in CBCT, including extinction, beam hardening, partial volume effect, aliasing, ring, and motion artifacts. These artifacts are caused by factors such as the discrete nature of the object, the cone beam geometry, and the limitations of the reconstruction algorithms. The Feldkamp algorithm, commonly used in CBCT, approximates line integrals and can lead to artifacts, especially at larger cone angles. Other factors, such as scatter and noise, also contribute to artifacts. The review also highlights the importance of understanding these artifacts for accurate diagnosis and the need for better reconstruction algorithms to reduce them. Despite the large body of literature on CBCT, there is a gap in knowledge between technical and radiographic communities, which can lead to diagnostic errors. The review emphasizes the need for improved understanding of the causes of artifacts and their effects to enhance the diagnostic accuracy of CBCT.Cone beam computed tomography (CBCT) is widely used in dentomaxillofacial radiology, but it is prone to artifacts due to discrepancies between mathematical modeling and the actual imaging process. Artifacts can interfere with diagnosis and are often mistaken for real structures. This review discusses the most common artifacts in CBCT, including extinction, beam hardening, partial volume effect, aliasing, ring, and motion artifacts. These artifacts are caused by factors such as the discrete nature of the object, the cone beam geometry, and the limitations of the reconstruction algorithms. The Feldkamp algorithm, commonly used in CBCT, approximates line integrals and can lead to artifacts, especially at larger cone angles. Other factors, such as scatter and noise, also contribute to artifacts. The review also highlights the importance of understanding these artifacts for accurate diagnosis and the need for better reconstruction algorithms to reduce them. Despite the large body of literature on CBCT, there is a gap in knowledge between technical and radiographic communities, which can lead to diagnostic errors. The review emphasizes the need for improved understanding of the causes of artifacts and their effects to enhance the diagnostic accuracy of CBCT.