A transition probability and Markov chain geostatistical approach is applied to synthesize the discrete permeability structure of moderately fractured rock. The approach can infuse either hard or subjective categorical information that is consistent with geological interpretations. The methodology is tested using data collected from the Moderately Fractured Rock (MFR) experiment area of the Underground Research Laboratory (URL) in southeastern Manitoba, Canada. Attributes pertaining to fracture location, frequency, and orientation along an array of boreholes intersecting the MFR experiment area, taken together with results from hydraulic response tests within packed-off intervals along the boreholes, are used to produce conditional stochastic realizations of hydraulic conductivity and effective porosity. Using the generated hydraulic conductivity and porosity realizations, we compare predicted tracer concentrations to the results of measured breakthrough data in a stochastic framework. The results show that solute migration behavior in moderately fractured rock can be successfully characterized and reasonably predicted upon careful error analysis of the results obtained from the various medium realizations synthesized from the conditional categorical descriptions of the fractured crystalline rock.