Exosuits are close-fitting devices, which are meant to be worn without restricting the motion of the user in the way that a rigid device would. These soft devices augment lower-limb biomechanics by using flexible, joint-spanning linear elements that are actuated to create moments about the spanned joints, effectively using the human body as the mechanical transmission from input to output. Consequently, the size of the moment arm that an exosuit creates about a given joint is dependent on the size and shape of the user, as well as their individualized gait patterns that depend on the terrain they are negotiating. These highly-variable human and environmental factors affect the performance of all soft exosuits (both passive and active), and the ability to quantify these effects would benefit assistive device development. In this work, we present a system for modeling the effects of user body mass index, biological sex, and gait kinematics on task-dependent exosuit performance. We use this system to estimate the performance of a hip-flexion exosuit over a range of body shapes obtained from a database of 3D human surface models, and with gait kinematics from physical experiments. Our results demonstrate that the user's body mass index, sex, and gait kinematics are necessary factors to consider when designing an exosuit for personalized assistance. This type of analysis can allow device developers to account for the unique shape and gait patterns of individuals, either in generating new designs, developing online control algorithms, or in configuring devices for specific individuals.