Previous literature has already discussed the effects of age and sex on the diagnosis and treatment of malocclusion problems. However, this effect varies among different ethnic groups. These differences have not yet been investigated in many populations, such as Arab orthodontic patients and residents of Israel. Therefore, it is crucial to understand such variations in specific populations for better diagnosis and treatment. The main aim of this study is to provide novel knowledge concerning skeletal classes I and II among a cohort of Arab patients who are citizens of Israel. We used parameters obtained from lateral cephalograms to understand the variations among different sex and age subgroups. We also examined the correlations and performed principal component analysis (PCA). This study was based on the coded records of 394 Arab patients diagnosed with skeletal Class I occlusion (SCIO) or skeletal Class II malocclusion (SCIIMO), according to the individualized ANB (Calculated_ANB) of Panagiotidis and Witt. Among patients with SCIO, males had a significantly more horizontal growth pattern (PFH/AFH) and anterior mandible rotation (ML-NSL) than females. Regarding patients with SCIIMO, female adults had more hyperdivergent jaw bases than adolescents (ML-NL) and a more posteriorly rotated mandible (ML-NSL). Spearman's analysis revealed many significant correlations, like Calculated_ANB, ANB angle, and Wits appraisal. The PCA results showed a remarkable ability to explain 88.6% of the sample variance using four principal components. This research revealed new information regarding Arab orthodontic patients diagnosed with skeletal class I or II. The results demonstrate the differences between the two classes. In addition, this study demonstrated the variation and correlation of cephalometric parameters among different sex and age subgroups in skeletal class I and II Arab patients, especially considering Calculated_ANB. Therefore, this study highlights the need to consider these differences when diagnosing patients and to distinguish the differences across different sex and age subgroups in the diagnosis and treatment process. Furthermore, the PCA results showed the importance of ML-NSL, SN-Pg, PFH/AFH ratio, and NL-ML in explaining the data variance.