Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by persistent deficits in social communication and interaction, alongside restricted and repetitive patterns of behavior. The prevalence of ASD has increased significantly over the last two decades, emphasizing the importance of timely diagnosis and intervention. Early diagnosis allows children to receive evidence-based therapies during critical periods of brain development, leading to improved developmental, educational, and social outcomes. This review examines contemporary approaches to early ASD diagnosis, including developmental surveillance, behavioral screening tools, neuroimaging techniques, genetic testing, and artificial intelligence-based diagnostic models. Furthermore, the study discusses barriers to early detection, disparities in healthcare access, and future directions for improving diagnostic accuracy. The findings suggest that integrating behavioral assessments with advanced technological approaches may significantly enhance early identification of ASD.