The challenge in predicting the movement of pesticides and other solutes in soil that exhibits preferential flow conditions is due to the variability in solute velocity through different flow paths. The generalized preferential flow model (GPFM) is a closed form solution to the convective dispersive equation, which combines these different flow paths into multiple groups (i.e. pore groups) with varying properties. The properties that vary between pore groups are limited to the solute velocity, dispersion coefficient, and the contribution to the solute transport. By using the GPFM to predict the solute transport in each pore group, it is possible to obtain an average concentration at any point in the soil profile. However, the GPFM lacks significant field-scale validation. In order to examine the viability of the GPFM, the predicted results of the model were compared to measured field-scale data. The measured data used to validate the GPFM was from field scale experiments by Gish et al. (2004) and Kung et al. (2000b and 2005). The experiments used conservative tracers, applied at the soil surface, and collected in the discharge of an underground drainage tile. One of these experiments took place at the Walworth County Farm in Elkhorn, Wisconsin and was a long duration, steady state experiment that revealed nearly the entire solute breakthrough at different irrigation rates. The other experiment was conducted at the South East Purdue Agricultural Center (SEPAC) in Butlerville, Indiana and was a short duration, transient flow situation in which tracers were sequentially applied during one experiment. In order to compare the results of the GPFM with the measured data, modifications were made to the model output to achieve a similar unit to that of the measured data. While modeling the transient flow experiments, other modifications were found to be necessary in order to model a transient process using steady state pieces. The modeling results from the steady state experiment show similar mass recovery rates with differences from the measured data of not more than 5% when the measured results were not affected by external circumstances. The transient flow results were significantly influenced by the water hydrograph for the system but were able to capture the trend of the solute leaching. These results show potential for further implementation of the model. The next step to be addressed is how to measure or systematically specify the modeling parameters.