In　a　multicenter　case-control　investigation,　we　assessed　the　efficacy　of　the　Electrooculogram　Signal　Analysis　(EOG-SA)　method,　which　integrates　attention-related　visual　evocation,　electrooculography,　and　nonlinear　analysis,　for　distinguishing　between　intellectual　and　developmental　disabilities　(IDD)　and　typical　development　(TD)　in　children.　Analyzing　127　participants　(63　IDD,　64　TD),　we　applied　nonlinear　dynamics　for　feature　extraction.　Results　indicated　EOG-SA＇s　capability　to　distinguish　IDD,　with　higher　template　thresholds　and　Correlation　Dimension　values　correlating　with　clinical　severity.　The　template　threshold　proved　a　robust　indicator,　with　higher　values　denoting　severe　IDD.　Discriminative　metrics　showed　areas　under　the　curve　of　0.91　(template　threshold)　and　0.85/0.91　(D2),　with　sensitivities　and　specificities　of　77.6%/95.9%　and　93.5%/71.0%,　respectively.　EOG-SA　emerges　as　a　promising　tool,　offering　interpretable　neural　biomarkers　for　early　and　nuanced　diagnosis　of　IDD.