The construction industry around the globe is afflicted with an exorbitant rate of fatal and non-fatal falls. To lower the propensity of the falls, researchers and safety experts have recommended to supplement the traditional passive fall safety measures with some active measures (such as early identification of task/environmental hazards and personal risk factors). Unfortunately, at present, there is no readily available onsite tool which could identify workers with poor postural controls. This study aimed to develop a static balance monitoring tool for proactive tracking of construction workers on-site using a wearable inertial measurement unit (WIMU) and a smartphone. To this end, a three-phase project was conducted. Firstly, a validation study was conducted to examine the validity of using WIMUs to detect task/fatigue-induced changes in static balance during a 20-second static balance test. The results of the study revealed that WIMUs could detect the post-task subtle changes in static balance with reference to the findings of a force-plate (considered as industrial standard). Secondly, since there were no existing static balance classification methods, five experts were engaged to establish balance classification thresholds using the fuzzy set theory. Thirdly, a mobile phone application was developed for the managers/foremen for onsite balance monitoring of the construction workers using the 20-second test at different times of the day and establishing their corresponding balance performance profiles. This would assist early identification of fall prone workers, plan mitigation schemes before a fall accident happens and ultimately help reduce falls in the construction industry.