(1) Background: This retrospective cohort study aimed to investigate the cephalometric evaluation of facial height ratio (FHR) and growth patterns. (2) Methods: We assessed facial height ratios, the y-axis to SN angle, and growth patterns in 94 participants from Timis County using digital cephalograms. Angle’s classification guided the categorization of participants. We digitally traced and analyzed cephalograms using the WebCeph imaging software. We conducted the statistical analysis using Python version 3.11.9. We performed the following statistical tests: Welch’s t-test or ANOVA (analysis of variance), Mann–Whitney U test or the Kruskal–Wallis test, χ² test or Fisher’s, and logistic regression. (3) Results: Significant correlations were observed between FHR and craniofacial development, especially in hypodivergent growth patterns. Among the molar classes, the most predominant growth pattern in Class I was normodivergent (61.5%), followed by hypodivergent (33.3%). In Class II, hypodivergent growth was the most common (52%), with a smaller proportion of normodivergent cases (30.8%). Class III was characterized by a mix of growth patterns, with hypodivergent being predominant (14.7%). Across all groups, the y-axis to SN angle remained within normal limits, and a strong negative correlation with Jarabak’s ratio was found (r = −0.72, p < 0.001). This shows the importance of using holistic assessment methods in orthodontic practice. (4) Patients from Timis County mostly have a hypodivergent growth pattern across all types of malocclusions. Understanding these patterns is essential for comprehensive orthodontic treatment planning. We need to conduct further research to investigate the implications of these findings on treatment outcomes and patient care.

(1) Background: This retrospective cohort study aimed to investigate the cephalometric evaluation of facial height ratio (FHR) and growth patterns. (2) Methods: We assessed facial height ratios, Y-axis to SN angle, and growth patterns in 94 participants from Timis county using digital cephalograms. Participants were categorized based on Angle’s classification. Cephalograms were digitally traced and analyzed using WebCeph imaging software. Statistical analysis was conducted using Python version 3.11.9. (3) Results: Significant correlations were observed between FHR and craniofacial development, particularly regarding hypodivergent growth patterns. In a sample of 94, molar classes showed varying patterns: Class I—33.3% hyperdivergent, 61.5% normodivergent, 33.3% hypodivergent. Class II—50% hyperdivergent, 30.8% normodivergent, 52% hypodivergent. Class III—16.7% hyperdivergent, 7.7% normodivergent, 14.7% hypodivergent. Y-axis to SN angle values were within normal limits across groups (Group I: 65.0 (IQR: 61.2-69.0), Group II: 65.0 (IQR: 62.0-69.0), Group III: 67.0 (IQR: 59.7- 69.0). A strong negative correlation was found between Y-axis to SN angle and Jarabak’s ratio (r = -0.72, p < 0.001), highlighting the need for holistic assessment methods in orthodontic practice. (4) Conclusion: Patients from Timis county predominantly exhibit a hypodivergent growth pattern across all malocclusion types. Understanding these patterns is essential for comprehensive orthodontic treatment planning. Further research is needed to explore the implications of these findings on treatment outcomes and patient care.

Any malocclusion can be associated with various face development patterns, including hyper, neutral and hypodivergent growth patterns. We measured face height ratios, angle formed by Y axis to SN and growth patterns in various malocclusions in a group of patients from Timis county. The pretreatment digital cephalograms of 350 participants were split into three groups based on Angle's classification of dentoalveolar malocclusion. Every cephalogram was digitally traced and analyzed using a composite cephalometric method analysis utilizing the WebCeph imaging cephalometric program, which included two linear and one angular. In general, patients from Timis county have a hypodivergent development pattern. Hypodivergent development pattern predominated in group I, II, and III. Group I hyperdivergent 5.14%, normodivergent 16.01%, hypodivergent 78.85%. Group II hyperdivergent 2.78%, normodivergent 14.44%, hypodivergent 82.78%. Group III hyperdivergent 10.53%, normodivergent 10.53%, hypodivergent 78.94%. In all three groups, the value of the angle formed by Y axis to SN is within normal limits group I 65.4 ±4.34°, group II 63.87± 3.86° and group III 64.66 ±5.28°. A strong negative correlation was found between angle: Y axis to SN and facial height ratio (r= -0,766; p <0.001). In all kinds of malocclusion, patients from Timis county show primarily a hypodivergent development pattern.