Technological advances in diagnosing tropical diseases have led to a paradigm shift, especially in resource-limited settings where accurate and timely diagnostics are essential. This chapter focuses on emerging diagnostic technologies—including point-of-care diagnostics, artificial intelligence (AI), portable molecular tools, and Clustered Regularly Interspaced Short Palindromic Repeats-based systems—in improving the accessibility, sensitivity, and speed of tropical disease diagnosis. Digital health platforms facilitate remote diagnosis, while AI supports faster and more accurate image analysis, which enhances early detection and individualized patient management. However, adopting these technologies faces challenges such as robust infrastructure, data privacy and ethical considerations, and regulatory frameworks to ensure safety and efficacy. Additionally, implementing these innovations requires investment in training, resources, and equitable distribution to underserved regions. Prospects lie in integrating genomic sequencing and AI-driven predictive models, which offer insights into pathogen evolution and resistance, ultimately strengthening global public health responses. As the worldwide community targets reductions in the burden of neglected tropical diseases, these diagnostic innovations will be crucial for achieving WHO’s goals for effective disease control and improved health outcomes.