Context: In Mexico's rural towns, it is essential to generate a culture of studying the prevalence of flat feet in children aged 3 to 5, whose arch is still in development and can be corrected. By means of a computer application, statistical bar graph and correlation studies via linear regression can validate the results obtained regarding the categorization of infants' footprint type, which are acquired through the Hernandez Corvo index (HCI), Clarke's angle protocol (CA), the Staheli index (SI), the Chippaux index (CI), and the body mass index (BMI). Methods: A statistical analysis of the plantar footprint of 95 infants in a rural region of Mexico was carried out, employing a computational technique together with a photo-podoscope. Footprint images were acquired, processed, and classified. The footprint type was categorized with respect to the HCI, CA, and the Staheli-Chippaux index (SCI). The footprint distribution was validated via the linear regression method. Results: We evidenced a prevalence of flat foot of 54,7% in relation to HCI, 58,9% in relation to CA, and 61,05% in relation to SCI, where the male gender was shown to be more susceptible (up to 28, 32, and 33 cases, respectively). The best prediction was obtained using the SI and the CI: 90,7 and 87,0% for the right and left feet, with a positive increase. No dependence on body composition was observed. Conclusions: The diagnosis of the type of footstep, in its normal, cavus, and flat categories, shows the prevalence of flat feet among infants aged 3 to 5, with at least 28 cases, mostly male and without dependence on weight. Although it is difficult to perform plantar footprint diagnoses in the rural communities of Mexico, this statistical study highlights the importance of monitoring foot development in preschool infants with the advantages and practicality of computational techniques.
