DENTAL VENEERS IN CONTEMPORARY ESTHETIC DENTISTRY:A SYSTEMATIC REVIEW OF CURRENT EVIDENCE

Background: Contemporary restorative dentistry offers multiple approaches for improving dental esthetics, among which veneers represent a minimally invasive and highly effective treatment modality. Their clinical success is influenced by material selection, preparation design, and adhesive protocols. Objective: To critically evaluate current evidence regarding the indications, preparation techniques, material types, clinical performance, and effectiveness of dental veneers. Methods: A systematic literature review was conducted using electronic databases including PubMed, Scopus, and Web of Science. Studies published between 2015 and 2025 were screened according to predefined inclusion and exclusion criteria. A total of 55 studies met the eligibility criteria and were included in the qualitative synthesis. Due to heterogeneity in study designs and outcome measures, a meta-analysis was not performed. Results: Dental veneers demonstrated consistently high esthetic outcomes, favorable long-term survival rates, and a conservative approach to tooth structure preservation. Ceramic veneers, particularly lithium disilicate and feldspathic porcelain systems, showed superior color stability, mechanical performance, and longevity compared with composite resin veneers. Although less durable, composite veneers offer advantages in cost-effectiveness and reparability. Preparation design was identified as a key determinant of fracture resistance and adhesive success, with enamel preservation significantly improving clinical outcomes. Conclusion: Dental veneers represent a reliable and predictable restorative option when appropriate case selection, conservative preparation design, and standardized adhesive protocols are followed. Ceramic materials remain the gold standard for long-term esthetic rehabilitation. Future research should focus on long-term randomized controlled clinical trials, standardization of preparation protocols, and integration of digital and AI-assisted workflows to enhance clinical predictability and outcomes.