<p>Lateral flow assays (LFAs) have emerged as indispensable analytical platforms for rapid, portable, and cost-effective detection in clinical diagnostics, food safety assessment, and environmental monitoring. Despite their broad applicability, conventional LFAs exhibit intrinsic limitations in analytical sensitivity, which restrict their capacity to detect low-abundance biomarkers typically present during early pathological stages. These shortcomings arise from rapid capillary-driven flow, limited analyte–receptor interaction times, suboptimal binding kinetics, and insufficient signal generation, collectively increasing the likelihood of false-negative results. Enhancing sensitivity therefore requires systematic optimization of factors governing LFA performance, including the physicochemical properties, orientation of biorecognition elements, membrane composition with porosity, strip geometry, sample matrix interactions, label characteristics, and operational conditions. This review provides a comprehensive analysis of state-of-the-art strategies aimed at improving LFA sensitivity, encompassing nanoparticle and label engineering, chemical and enzymatic signal-amplification methodologies, advanced membrane and strip design, flow-rate modulation, sample pre-treatment and enrichment procedures, aptamer- and nanobody-based recognition systems, and multiplexing architectures. Additionally, emerging hybrid platforms that integrate microfluidics, engineered materials, or digital quantification demonstrate significant potential for approaching laboratory-level detection limits. While these innovations markedly advance LFA performance, challenges persist regarding cost, manufacturability, module integration, and preservation of user operability. This review delineates the translational pathway toward next-generation high-sensitivity LFAs for robust point-of-care (POC) diagnostics.</p> Graphical Abstract <p></p>