Rock fractures and veins have been well documented by the Curiosity rover in the lithologies within Gale crater, Mars, and an understanding of the rock mechanical properties of Mars analog samples will improve our capabilities to predict fracture formation conditions (e.g., burial depth and influence of fluids). Data collected by Curiosity's drill allow estimation of unconfined compressive strength (UCS) for rocks that have been sampled by the drill. These estimates reveal that the drilled rock types are considerably weak. Qualitative assessments of rock types that were not drilled, however, suggest that stronger lithologies also exist within Gale crater. Here we integrate experimental testing, computational simulation, and uncertainty quantification to evaluate a predictive approach using the UCS obtained from the rover to determine a suite of mechanical properties for Gale lithologies. This method is demonstrated using analog rocks, specifically iron‐cemented sandstone and poorly lithified mudstone. The range of properties determined from sandstone testing is consistent with very strong terrestrial lithologies, and mudstone testing is consistent with extremely weak lithologies, both representative of rock types identified in Gale crater. We evaluate the use of established correlations between measured properties and quantify the uncertainty in using predicted properties to simulate fracture through analog lithologies. Sensitivity analysis indicates the properties of tensile strength and fracture energy derived from the UCS are highly influential properties in predicting fracture. The predictive approach was successful for a well‐sorted and well‐cemented fine sandstone with no visible porosity and exhibited substantially large errors for analog eolian siltstone lithologies. Plain Language Summary Fractures have been well documented by the Curiosity rover in rock units exposed within Gale crater, Mars, and an understanding of the mechanical properties of these rocks is necessary to predict the conditions of fracture formation. On Mars, however, our understanding of rock properties is restricted by a paucity of information on rock composition, limited access to samples for contact science, and a lack of quantitative mechanical data. It is therefore essential to develop the technology to predict a full suite of mechanical properties from available Mars rover data. To advance the potential of such technology on future rovers, we investigate the properties of Mars analog rock types, predict a full range of properties from rock strength, and quantify the uncertainty in this predictive method in order to identify the key factors that influence fracture formation.
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