Suspended-load backpacks have been proposed as a way to provide power for small electronic devices by capturing the mechanical energy generated by the vertical movement of the suspended load and converting it into electrical energy. The aim of the current study was to build a base excitation model able to predict the relative velocity of the load (an index of the amount of harvestable energy of such a system) using as inputs the mass of the suspended load, the walking speed and the leg length of the user. Nine human participants walked on a treadmill under two load conditions (15.8 kg and 22.6 kg load) and three walking speed conditions (1.16 m/s, 1.43 m/s and 1.70 m/s). The predictions of the load velocity by the base-excitation model under these conditions were then compared with the measured load velocity. The results of this study showed a moderately strong correlation (0.76) between the root mean square of the predicted and measured relative velocity of the load, and the average absolute error of these predictions was 24.2%. These results provide support for the utility of this approach and also provide motivation for further refinement of the base excitation model for the prediction of the amount of energy able to be harvested from suspended-load backpack systems.