Educational supervision plays a crucial and pivotal role in improving instructional quality and strengthening school performance, especially in the context of 21st-century education where demands for global competitiveness, digital integration, and outcomes-based practices continue to grow. In this evolving landscape, supervisors are expected to go beyond administrative functions and demonstrate strong instructional leadership, technical expertise, and data-driven decision-making. This study examined the relationship between supervisors’ skills, competencies, instructional practices, and job performance, and used the findings to develop a competency-based technical assistance model. A descriptive–correlational–developmental research design was employed, involving 114 respondents selected through stratified random sampling. Data were gathered using a researcher-made survey and analyzed using descriptive statistics, Pearson’s correlation, and multiple regression. Results showed that supervisors demonstrated very high levels across all domains. More importantly, the findings revealed significant relationships among skills, competencies, instructional practices, and job performance, indicating that these elements work together in a mutually reinforcing manner. Regression analysis further confirmed that these factors collectively predict job performance, underscoring their combined influence on effective supervision. Based on these results, a competency-based technical assistance model was developed to translate these insights into practical strategies for professional support and development. The study highlights that effective supervision is not defined by isolated competencies but by the dynamic interaction of key professional attributes. Strengthening these interconnections through targeted interventions can enhance instructional leadership and contribute to sustained improvements in educational outcomes.