The study of Source-to-Sink systems is an important field of research focused on understanding the entire process of material transport from source areas like mountain ranges or other landforms to sink areas like river basins, lakes, and oceans. This process entails weathering of the parent rock, erosion of materials, transportation via various agents (such as wind, water, or ice), and eventual deposition at sink locations. Analyzing this system reveals dynamic surface changes, material cycling mechanisms, and how these processes adapt to environmental shifts over time. Understanding these complex processes is crucial for a variety of scientific fields, including geomorphology, environmental science, and natural resource management; however, the traditional methods such as field observations and laboratory analyses, Have their own set of challenges. Data availability, low spatiotemporal resolution, and ambiguity in interpretation make it difficult to capture the rapid and dynamic changes occurring in natural systems. Furthermore, these methods are not ideally suited for analyzing long-term evolutionary processes or large-scale systems. Consequently, numerical modeling has emerged as an essential tool studying source-to-sink systems, addressing these traditional limitations by simulating complex processes over varying spatial and temporal scales. They offer more quantitative insights into the dynamics of erosion, transport, and deposition under different environmental conditions.This paper reviews five key numerical tools commonly used in source-to-sink research: Dionisos, SEDSIM, Landlab, goSPL, and Delft3D. Each tool has specific advantages that render it suitable for various research purposes. Dionisos, for instance, excels at modeling large-scale, long-term basin-filling processes though it is less effective for simulating small-scale, dynamic changes. SEDSIM, based on hydrodynamic equations, produces highly accurate results for clastic sedimentary processes, but tends to be slower and more focused on specific types of sediment. LandLab is highly customizable and capable of multi-process simulations; although, it requires advanced programming skills. goSPL handles global-scale high-resolution simulations effectively, despite struggling with localized phenomena and requiring significant computational resources. Delft3D is ideal for small-scale, fine-detail simulations, particularly in coastal, riverine, and lacustrine environments, although it faces challenges in large-scale applications. With ongoing advances in computational power and algorithms, future advancements in source-to-sink modeling are expected. The integration of big data and AI will likely enhance the accuracy of predictions, facilitate multidisciplinary integration, and drive the intelligent evolution of the field.