This chapter introduces neural networks for content-based image retrieval (CBIR) systems. It presents a critical literature review of both the traditional and neural network-based techniques that are used to retrieve images based on their content. It shows how neural networks and fuzzy logic can be used in the interpretation of queries, feature extraction, and classification of features by describing a detailed research methodology. It investigates a neural network-based technique in conjunction with fuzzy logic to improve the overall performance of CBIR systems. The results of the investigation on a benchmark database with a comparative analysis are presented in this chapter. The methodologies and results presented in this chapter will allow researchers to improve and compare their methods, and it also will allow system developers to understand and implement the neural network and fuzzy logic-based techniques for content-based image retrieval. © 2007, Idea Group Inc.