To estimate the probability of causation (PC) under the Energy Employees Occupational Illness Compensation Program Act (EEOICP A), it is necessary to reconstruct the dose for the tissue or organ that was diagnosed with a primary cancer. Since EEOICPA provides compensation if the PC is 50% or greater at the 99% confidence interval, uncertainty in the organ dose is an important parameter that must be considered. This paper discusses a Monte Carlo approach used to estimate the organ dose uncertainty from three sources: 1) random error in the measured dose from multiple dosimeters; 2) uncertainty in missed dose due to limits of detection or reporting thresholds; and 3) uncertainty in the organ dose conversion factor (DCF). The uncertainty in the dose conversion factors are due to incomplete knowledge of the photon energy and exposure geometry. The Interactive RadioEpidemiology Program (IREP) uses three photon energy intervals to calculate the PC. Since the true photon energy spectrum is almost never known, especially with early dosimetry, and the organ dose conversion factors vary significantly across the photon energy intervals, there is considerable degree. of uncertainty in these dose conversion factors. In addition, the exposure geometry for an individual worker is also almost never known with certainty. Through a qualitative evaluation of the workplace and the job, the most probable exposure geometry is estimated. The possible distribution of dose conversion factors is bounded using the photon energy' interval and exposure geometry combination that results in the lowest organ dose conversion factor and the combination that results in the highest organ dose conversion factor. Using Monte Carlo sampling of the distributions of measured dose, missed dose, and dose conversion factors, the total uncertainty in the tissue or organ dose is evaluated. This approach is currently used to determine external organ dose uncertainty in accordance with 42 CFR part 82.