Objective: To carry out a comparative study on effective clinical decision-making tools between Canadian Assessment of Tomography for Childhood Head injury, Pediatric Emergency Care Applied Research Network (PECARN) and Children's Head injury Algorithm for the prediction of Important Clinical Events in pediatrics head trauma cases. Study Design: Validation study. Place and Duration of Study: Department of Surgery, Saif Shaheed Hospital, Haveli Kahota, Azad Kashmir, Pakistan, from Oct 2021 to Nov 2022. Methodology: One hundred and fifty paediatric patients suffering from minor head injury were evaluated on clinical intervention decisions as per emergency procedures during the period of study. Sensitivity, Specificity, Positive Predictive Value and Negative Predictive Value of the selected diagnostic tests was checked. Results: Based on the head CT positivity, PECARN was found to be 81.8% sensitive and 61.9% specific. Canadian Assessment of Tomography for Childhood show sensitivity of 90.9 % and specificity of 65.5%. CHALICE had sensitivity and specificity of 63.6% and 61.5% respectively. CHALICE was unable to identify a pathological CT result with statistical significance (p=0.17) however PECARN and CATCH rule proved significant (p<0.05). CATCH rule show highest positive predictive score of 17.2% and negative predictive score of 98.8%. Conclusion: PECARN, CATCH, and CHALICE criteria are effective in deciding whether or not to perform Computerized Brain Tomography (CBT) scans on children with MHT, leading us to believe that employing these criteria could prevent unnecessary CBT scans.