Background <p>Early identification of cranial deformities in infants is essential for timely intervention and preventing long-term complications. In Uganda, particularly in rural areas, access to specialised paediatric healthcare remains limited, making it difficult to diagnose and manage cranial abnormalities early. This study takes a unique approach by using the PhotoMeDAS system. This non-invasive technology allows accurate cranial measurements through QR-based imaging to define normative cranial index ranges for Ugandan infants. By analysing key cranial parameters associated with head shape, symmetry, and overall growth patterns, this study aims to establish reference values that can serve as a baseline for clinical assessments.</p> Methods <p>A cross-sectional study was conducted in healthcare centres in Lugazi, Uganda, collecting cranial measurements from 195 infants aged 0–2 years old. The data was collected using the PhotoMeDAS system, a non-invasive technology that allows accurate cranial measurements through QR-based imaging. The primary cranial variables analysed included Head Circumference (HC), Cephalic Index (CI), Cranial Vault Asymmetry Index (CVAI), Pseudovolume (PV), and Frontal Angle (FA). HC was measured to establish general growth patterns, while the CI provided insights into head shape classification (dolichocephalic, mesocephalic, or brachycephalic). The CVAI assessed cranial symmetry, detecting potential cases of plagiocephaly, while the PV evaluated the proportionality of cranial growth relative to the perimeter. Finally, the FA was considered to assess anterior cranial development and forehead morphology.</p> <p>For the management and optimisation of processes, Microsoft Visio was used to create flow diagrams that facilitated the organisation of the paediatric campaign. SPSS and Excel were employed for statistical analysis, evaluating the relationship between cranial indices and variables such as sex, age, and ethnicity. Normality tests (Kolmogorov-Smirnov), chi-square tests, and ANOVA were applied to identify distribution patterns and significant variations among subgroups. In addition, Python was used to process cranial images obtained during the paediatric research.</p> Results <p>This study provides the first normative dataset for cranial indexes in Ugandan infants, highlighting significant variations in head morphology according to age and sex. The CI revealed a predominantly mesocephalic distribution, with a small proportion of dolichocephalic and brachycephalic cases. The CVAI showed a low prevalence of significant asymmetry, suggesting minimal cases of plagiocephaly in the sample. The PV indicated proportional cranial growth trends, with expected increases in head size over time. The FA exhibited slight variations across age groups, reflecting dynamic changes in forehead development during early childhood. These findings have the potential to impact healthcare practices significantly, guiding early diagnosis and intervention strategies for cranial deformities in Ugandan infants.</p> Conclusion <p>This study fills a crucial gap in paediatric cranial morphology research by establishing the first cranial index reference values for Ugandan infants. These findings provide essential data for healthcare professionals to facilitate early diagnosis, guide preventive strategies, and improve clinical assessments in low-resource settings where specialised care is scarce. Further research is needed to investigate genetic and environmental influences on cranial development and compare these normative values with populations from different geographical and ethnic backgrounds. This emphasis on the need for further research suggests the potential for future developments in the field.</p>