This work investigates a novel iron Fischer-Tropsch (FT) catalyst preparation and describes the development of a trickle fixed-bed recycle reactor model (TFBRRM) for the FT synthesis applicable to both iron and cobalt catalysts. The iron catalyst preparation was developed using a novel solvent deficient precipitation reaction. Fifteen Fe/Cu/K/SiO2 catalysts were prepared to investigate key preparation variables including timing of promoter addition, washing or not washing after precipitation, and drying temperature. Adding promoters to starting materials before precipitation (1S) gives more uniform promoter distributions which gives higher water-gas shift activity and lower methane selectivity. Unwashed catalysts have smaller average pore and crystallite diameters (3.9-10.8 nm versus 15.3-29.5 nm) and 30% smaller pore volumes, but 65% higher rates of reaction than washed catalysts. Catalysts dried first at 100 °C have up to 50% smaller average pore and crystallite diameters, but 10-20% higher rates of reaction than catalysts dried first at 60 °C. Overall, 1S catalysts, left unwashed, and dried first at 100 °C are best suited in activity, selectivity, and stability for wax production from hydrogen-deficient feed stocks such as coal, biomass, or municipal waste. The activity of the most active catalyst of this study is greater than or equal to the activities of two of three catalysts reported in the literature. This dissertation describes in detail the TFBRRM, reports its validation, and presents results of varying fundamental, theoretically-based parameters (e.g. effective diffusivity, Prandtl number, friction factor, etc.) as well as physical process parameters (i.e. recycle ratio, pressure, flow rate, tube diameter, cooling temperature, and pellet diameter and shape). For example, the model predicts that decreasing effective diffusivity from 7.1E-9 to 2.8E-9 m^2/s results in a lower maximum temperature (from 523 to 518 K) and a longer required bed length to achieve 60% conversion of CO (from 5.7 to 8.5 m). Using the Tallmadge equation to estimate friction losses as recommended by the author results in a pressure drop 40% smaller than using the Ergun equation. Validation of the model was accomplished by matching published full-scale plant data from the SASOL Arge reactors.