ontology is a formal explicit description of concepts in the knowledge domain. in recent years, developing ontology in different domains is a hot topic for many researchers, especially in the medical field because of the benefits offered to users. using ontology allows sharing and reusing domain knowledge in an efficient and explicit way. in particular, ontology in medical field can facilitate the access to query data, precise knowledge, and seamless sharing of electronic medical records (emr). thus ontology increases the accuracy of doctor’s diagnostic decision. autism spectrum disorder (asd) often presents with difficulties in verbal and nonverbal communication, behavior and social interactions. autism is difficult to define due to the complex heterogeneous disorders in this domain and to the lack of coherent set of knowledge that deals with all aspects of autism. the purpose of this research was to address these shortcomings by developing a comprehensive asd ontology that formally conceptualizes both domain and operational autism knowledge, unifies autism terminology, and facilitates access to precise autistic information for both general public and expert users, thus enabling better diagnostic and treatment decisions. to build such ontology, we investigated many medical research works in the various areas of autism such as disorders, effects and treatments of asd. the study was done with the purpose of extracting and gathering information from the most trusted sources such as existing ontologies, standard textbooks, relevant articles and clinical studies. these sources were used to build a semantic map linking key concept classes. mainly we focused on properties and relationships between these classes to formally describe the autistic domain and operational knowledge and to bring the scattered knowledge into the ontological form. ontology instantiation for each subclass was based on pilot studies and clinical cases. the system was implemented using protégé, an ontological framework developed by the stanford center for biomedical informatics research at the stanford university. the ontology was built using the web ontology language (owl). owl is a semantic web language designed to indicate the rich and complex knowledge of the domain. moreover, we developed a basic web query system for the asd ontology to present the ontology information to different users around the world. the developed system has been evaluated to measure quality of embedded knowledge, ontology correctness and the usability of its web query system.