The increasing prevalence of diverse human diseases has heightened global interest in algae and their potential therapeutic applications. In this context, in silico analysis emerges as a valuable, time- and cost-effective method for identifying promising therapeutics from the vast array of natural metabolites present in algae. In this chapter, we explored the integration of molecular docking and molecular dynamics (MD) simulations in the study of algae and their metabolites as therapeutics to date. Molecular docking serves as a pivotal tool in predicting the binding affinity and orientation of these metabolites to target proteins, facilitating the identification of potential drug candidates, especially from a large dataset. This prediction is, however, an estimate with a degree of uncertainty. Therefore, complementarily, MD simulations provide an estimated value that helps provide dynamic insights into the stability and behavior of these molecular interactions over a given time frame. Through detailed case studies, we illustrate the successful application of these computational techniques in uncovering the therapeutic potential of algae, particularly as antihypertensive, anti-inflammatory, antiviral, antibacterial, antioxidant, and anticancer treatments. These computational methods have enhanced the efficiency and accuracy of drug discovery processes, paving the way for novel therapeutic agents derived from algae. Future perspectives and emerging trends in this interdisciplinary field are also presented, underscoring the importance of continued research and innovation.