Abstract: The advancements in multimedia technologies have highlighted the demand to retrieve images among several images. Also, the need for accurate image retrieval is forced to development of more efficient methods. Nowadays, Content-Based Image Retrieval (CBIR) became an active research field, to produce typical solutions for similar images retrieval from image databases. Further, CBIR became the main direction for image retrieval, likewise the bag-of-visual- word model (BoVW), which is a popular helpful model for achieving CBIR goals. In this paper, a CBIR survey had been presented, the focus had pointed to the BoVW Model used for CBIR and a brief discussion about the different techniques of BOVW and the role it plays in computer vision technology and image enhancement systems. For the last three decades, the semantic gap between high-level semantic and low-level image features is an active research area in CBIR, hence, the BoVW model is one of the mechanizes utilized for reducing the semantic gap. Further, the BoVW model, as a significant CBIR model, is fused with many useful methods. CBIR popular methods, such as SIFT and SURF, are worked for general image types. Although, other specific methods are used either for medical images or for streaming images. In this work, various methods of different types have been presented. However, most CBIR researches had considered the BoVW model with general-purpose CBIR, specific purpose methods and benchmarks had been studied. Keywords: SEMANTIC GAP; BAG OF VISUAL