Early identification of Attention-Deficit/ Hyperactivity Disorder (ADHD) is imperative for individuals with this disorder to manage their challenges and improve their quality of life effectively. However, the neural mechanisms and brain network changes underlying ADHD are not yet fully understood. The Human Brain is functionally organised by brain patterns that have spatially distinct but functionally connected that were discovered at rest, known as Resting-state networks (RSNs). Resting-state functional magnetic resonance imaging (rs-fMRI), is an incredible tool that advanced us with detailed insight into those RSNs. Researchers use brain atlases to define RSN nodes for further analysis. Unfortunately, most atlases rely on data from healthy individuals, leading to inconsistencies and a lack of disease-specific atlases tailored for populations with specific medical conditions. Researchers have started developing disease-specific brain atlases or modifying existing ones to represent the disease-specific brain connectivity patterns better. To address the mentioned gaps, this study introduces “Hexa-Net” ADHD-specific brain reference after (1) generating a Master spatial atlas after conducting a systematic comparison of five priori brain atlases and six Network-of-Interests (NoIs) that are frequently referenced in ADHD literature: (Auditory- (AUN), Cognitive Control- (CCN), Dorsal Attention-(DAN), Default Mode-(DMN), Sensorimotor-(SMN), and Ventral Attention-(VAN)) Networks, resulted in overall spatial overlap ranges from (30-97%) across them. (2) demarcating NoIs after measuring the spatial distribution and temporal dynamics of NoIs quantified by the ADHD200 dataset. Findings reflect a high correlation between the spatial composition of the six RSN associated with Functional Connectivity. Hexa-Net may serve as a valuable tool for future ADHD studies.