Measuring trunk posture in the workplace commonly involves subjective observation or self-report methods or the use of costly and time-consuming motion analysis systems (current gold standard). This work compared trunk inclination measurements using a simple data-logging inclinometer with trunk flexion measurements using a motion analysis system, and evaluated adding measures of subject anthropometry to exposure prediction models to improve the agreement between the two methods. Simulated lifting tasks (n=36) were performed by eight participants, and trunk postures were simultaneously measured with each method. There were significant differences between the two methods, with the inclinometer initially explaining 47% of the variance in the motion analysis measurements. However, adding one key anthropometric parameter (lower arm length) to the inclinometer-based trunk flexion prediction model reduced the differences between the two systems and accounted for 79% of the motion analysis method's variance. Although caution must be applied when generalizing lower-arm length as a correction factor, the overall strategy of anthropometric modeling is a novel contribution. In this lifting-based study, by accounting for subject anthropometry, a single, simple data-logging inclinometer shows promise for trunk posture measurement and may have utility in larger-scale field studies where similar types of tasks are performed.