A wideband extension of the Optimum Uncertain Field Processor (OUFP) is presented. Combined with Monte Carlo estimation methods, this processor provides a fast, efficient, and robust technique for Matched-Field Processing (MFP). Under a simulated Hudson Canyon environment, a quantitative, probabilistic analysis of the sensitivity of the Optimum Matched-Field Processor (OMFP) to various kinds of environmental mismatch is shown. Similarly, the performance of the OUFP is calculated. Finally, the optimum wideband OUFP is applied to a data set collected from the Hudson Canyon, the results tabulated, and then compared to a standard Bartlett processor. The performance of the optimum wideband OUFP and the suboptimum Bartlett processor are in very good agreement with the performance predicted from simulation results.