Accurate surface fuel load estimates based on the planar intercept method require a considerable amount of time and cost. Recently the photoload method has been proposed as an alternative for sampling of fine woody surface fuels. To evaluate the use of photoload fuel sampling, six simulated fuel beds of 100 photoload visual estimates and destructively sampled fuel loads were generated at three levels of fuel loading (0.016, 0.060, and 0.120  kg  m–2) and two levels of variability (coefficients of variation of ~42 and 85%). We assessed the accuracy and precision of simple random sampling with and without double sampling on surface fuel load estimation. Direct visual estimates often overestimated fuel loads where actual fuel loading was low and underestimated fuel loads where fuel loads were large. We found that double sampling with a classical regression estimation approach provided the most accurate and precise fuel load estimates, substantially improving the accuracy and precision achieved over standard photoload estimation when n ≥ 20 and double sampling rate ≥20%. These results indicate that fine woody fuel loading estimation with the photoload technique can be improved by incorporating a double sampling approach.