Continuous milli-scale and micro-scale structures such as FlowPlate® microreactors have emerged as a promising element of process intensification due to their inherently effective rates of mass and heat transfer. These microfluidic devices have proven to be a preferred solution in place of energy-intensive batch processes for certain pathways of fine chemical and pharmaceutical synthesis, most notably fast reactions taking place on the scale of milliseconds to seconds. Computational fluid dynamics (CFD) has become an increasingly valuable tool in the field of microreactor design and optimization for its ability to locally map complex fluid flow patterns and resolve microscopic scales of reactive mixing that are challenging to characterize experimentally. The primary objective of this research was thus to develop and validate a mathematical model for the simulation of chaotic flow and homogeneous mixing in continuous microreactors. The model needed to be versatile enough to handle transition between flow regimes within a given reactor as well as the coexistence of both chaotic and laminar flow patterns in the micromixing elements that comprise said reactors. This was successfully achieved through the implementation of a k-ω SST (shear-stress transport) turbulence model that accounts for the impact of small-scale temporal and spatial fluctuations generated in the micromixer geometries studied herein; be it a liquid-liquid mixer (LLM), a serpentine (SZ) or a tangential (TG) mixer. In a first CFD study, the computational predictions were validated based on excellent agreement with experimental pressure loss (R^2 > 0.997) and residence time distribution (RTD) data (R^2 > 0.97) in several LL microreactors at Reynolds numbers ranging from 210 to 2140. Furthermore, the local velocity distribution and streamlines were mapped across the 3D domain of these reactors and it was discovered, based on the emergence of advective recirculation zones and turbulent dispersion, that a drastic change in flow behaviour occurred in these mixing elements at a Reynolds number of about 640. The interspacing of LLM elements with straight microchannels proved to be a suitable approach to modulating pressure loss while concurrently maintaining the chaotic secondary flow patterns generated from the mixers. In a second CFD study, the impact of micromixer geometry on the local velocity fields and advective transport performance was investigated both from a macromixing and micromixing perspective. Like the LLM, the SZ and TG mixers conferred chaotic secondary flow patterns at characteristic Reynolds numbers between 500 and 1000. As such, it was concluded that it would be ideal to operate these mixers at water flow rates of at least 30 ml/min. Contour plots of the velocity magnitude coupled with the computation of RTD showed that the SZ virtually mimics a plug-flow profile over a volume of 77 mm3 or greater at 50 g/min. The RTD of the LLM and TG resembles that of a mixed flow pattern given that approximately 65-80% of their fluid volume is occupied by recirculation zones. As such, it required 65 LLMs in series (3105 mm3) and 80 TGs (1142 mm3) to approach the same pattern as 10 SZs (77 mm3) from a macromixing perspective. Micromixing time distributions (MTD) were also characterized by locally computing the decay time of small-scale segregation (t_SSS) as a function of flow rate, wherein higher flow rates generated lower characteristic mixing times. The TG and LLM conferred the broadest range of mixing times, spanning nearly four orders of magnitude in the range of [0.02 ms, 10 ms], whereas the SZ generated a much narrower MTD ranging between [0.024 ms, 0.69 ms]. Finally, the impact of geometry and flow conditions on reaction yield was assessed by characterizing the extent of a finite-rate reaction relative to an infinitely fast reaction taking place in parallel. The calculated yield for the competitive-parallel reaction scheme showed that the second Damköhler number (Dall) computed based on the mean tSSS provides useful information about whether the process will be limited by the intrinsic rate of reaction or by the rate of mass transfer, even though the reaction process is controlled by a combination of the RTD as well as loss of LSS and SSS. It was concluded that the change in MTD as a function of power dissipation should coincide with the reaction yield response, and that any deviation in that relationship is because of macroscopic blending of reactants in the entrance region.