Precipitation is a process wherein a solid phase forms from a solution. Precipitation is at the heart of many industries producing pharmaceuticals, catalysts, ceramics, and nanoparticles. In addition to being a material synthesis route, precipitation has important applications as a separation process and in the setting of cements. The overall goal of this thesis is to advance good practices for studying the process of precipitation from liquid solutions. Special attention is paid to combining experimentation with theory and maximizing the potential of each method. To demonstrate the variety of techniques one may have to use, we focus on two different model systems, namely calcium-silicate-hydrate (C-S-H) and colloidal gold. C-S-H is the most important product of cement hydration, which has also found application in biomedicine, environmental clean-up, and very recently catalysis. Colloidal gold is another strategic material with widespread application in the medical sector, consumer electronics and optics, and catalysis. In all these applications, the properties of the final product such as particle size distribution, morphology, surface area, and composition govern its performance. Fine-tuning of these properties is not possible unless we have a thorough understanding about the formation process mechanism. In this thesis, first we address the complexity of C-S-H formation by regressing a model based on the population balance equation—embracing primary nucleation, anisotropic catalytic secondary nucleation, and molecular growth—to experimental kinetic data. The merit of the proposed pathway and the output was carefully examined in the light of previous literature and new insight was provided about the genesis of mesoscale structure in C-S-H. Several mechanistic aspects including the energetics of different processes, the potential mechanism of growth, and the underlying phenomena producing the hierarchical structure of C-S-H were prudently studied and explained. Next, we present a more in depth analysis of the abovementioned computational framework addressing the model behaviour in response to uncertainty in its parameters. This was done via uncertainty/sensitivity analysis (UA/SA) based on three complementary techniques. We then continued by exploring the possibility of applying UA/SA to rationalize the design of nanoparticle synthesis process with C-S-H as a model system. We identified reasonable trends for optimizing the product properties, with specific surface area of particles as a design target. In particular, we showed a clear dependence of the design target on the reagent addition rate in a semi-batch reaction scheme. In the last topic, we study the seeded growth of gold nanoparticles (GNPs). Here, the focus was on collecting appropriate experimental data—using in situ UV-vis spectroscopy—that can later be used for kinetic modeling as was done for C-S-H. We identified the inadequacy of the currently available optical models and developed a comprehensive framework based on the physical characteristics of the process. We discussed that, counterintuitively, an apparently simple seeded growth process is a competition between several phenomena such as primary and secondary nucleation, molecular growth, agglomeration/aggregation, and ripening. This was supported by compiling the available literature information as well as using a model-free, data-driven principal component analysis.