Augmented Reality (AR) technology has revolutionized how users interact with digital content in real-world environments. However, ensuring the quality of AR experiences remains a complex challenge due to the diverse factors influencing user perception and satisfaction. To address this challenge, researchers and developers are turning to conceptual models that provide structured frameworks for evaluating and optimizing AR quality. This paper explores the development of such a conceptual model, aiming to define the scope, objectives, and metrics for assessing AR quality comprehensively. By considering components such as visual fidelity, interaction responsiveness, spatial alignment accuracy, and semantic coherence, the model seeks to provide a systematic approach to AR quality assessment. Additionally, factors such as hardware capabilities, software optimization, user interaction design, and environmental conditions are integrated into the model to capture their influence on AR quality. Despite promising advancements, challenges such as model simplicity, subjectivity in metrics, and validation remain. Through ongoing research and refinement, the proposed conceptual model aims to enhance AR development practices, foster innovation, and improve user satisfaction across diverse AR applications and environments.