Autism, also known as autism spectrum disorder (ASD), is a neurodevelopmental condition associated with differences in emotional processing and social communication. Electroencephalogram (EEG) analysis presents a unique avenue for exploring its underlying neural evolutionary mechanisms. To this end, this study explored the similarities and differences in emotional processing between children with ASD (ASD group) and those without ASD (control group) using EEG. The final analysis included 45 children: 22 with ASD (mean age = 5.29, age range: 2–8) and 23 without ASD (mean age = 4.37, age range: 2–6). EEG signals were synchronously collected during stimulation with a series of emotional videos. The t-tests on the collected EEG data were performed to determine any statistical differences in power spectral density, sample entropy, and differential entropy values between the groups. A functional connectivity analysis was also performed for a more comprehensive understanding. SHapley Additive exPlanations (SHAP) were applied to validate the findings, ensuring their robustness and reliability. The results showed that the ASD group exhibited reduced beta-band activity in the frontal regions and enhanced delta-band activity in the temporo–occipital areas compared to the control group. Entropy analyses revealed lower brain complexity in the ASD group. Functional connectivity results showed increased high-frequency synchronization in the ASD group but more coordinated low-frequency connectivity patterns in the control group. Moreover, the application of SHAP-based analysis with XGBoost confirmed the significance and predictive value of beta- and delta-band features in the frontal and occipital regions, providing potential biomarkers for distinct emotional processing in individuals with ASD. Overall, this study holds potential to facilitate the understanding of the neuronal mechanisms underlying emotional processing in individuals with ASD and inform the development of targeted neurotherapeutic interventions.