This project aims to develop capabilities, including interfaces with existing tools, for uncertainty assessment in biomechanics applications. Often, deterministic predictions fail to capture, or assess, the potential variability induced by unknown or distributed inputs. Probabilistic methods represent one avenue to address this issue. First, an interface with an existing probabilistic tool, Dakota, will be developed to efficiently prescribe distribution based inputs for subsequent analysis. The framework will be applied to computational predictions of joint and tissue mechanics but could be utilized in many different types of analysis. Tools will also be developed and distributed when existing software packages fail to meet the desired capabilities.