<p>Lung disease is a major global public health challenge characterized by high mortality and significant diagnostic complexity due to overlapping clinical symptoms among diseases with distinct etiologies. Conventional diagnostic methods, such as chest imaging and sputum culture, often suffer from insufficient sensitivity for early detection or prolonged results that delay therapeutic intervention. As a promising alternative, aptasensors have emerged as powerful next-generation diagnostic tools due to their high target selectivity and structural stability. This review comprehensively summarizes recent advancements in aptasensor technologies for diagnosing major lung diseases, including pneumonia, tuberculosis, lung cancer, and asthma. It systematically analyzes research trends focusing on target biomarkers, signal transduction mechanisms, and functional nanomaterials while providing a comparative perspective on design strategies tailored to the distinct etiological mechanisms of each disease. Furthermore, this review addresses current technical hurdles such as matrix effects and long-term stability. Prospective directions for developing comprehensive multi-marker detection panels integrated with advanced nanomaterials and automated analytical systems are proposed to facilitate the molecular interpretation of complex pulmonary pathophysiology. This review provides a comprehensive overview to aid researchers in establishing next-generation diagnostic platforms that seamlessly integrate with clinical workflows.</p>