olecular replacement phasing of macromolecular crystal structures is often fast, but if a molecular replacement solution is not immediately obtained, the crystallographer must judge whether to pursue molecular replacement or attempt experimental phasing as the quickest path to structure solution. The introduction of eLLG (expected log-likelihood gain (McCoy et al., 2017)) has given the crystallographer a powerful new tool to aid in making this decision. The eLLG is LLGI (log-likelihood gain on intensity (Read & McCoy, 2016)) expected from a correctly placed model. It is calculated as a sum over the reflections of a function dependent on the fraction of the scattering for which the model accounts, the estimated model coordinate error, and the measurement errors in the data. We show how eLLG is used to answer the question "Can I solve my structure by molecular replacement?" However, this is only the most obvious of the applications of eLLG. We also discuss how eLLG is used for determining search order, minimal data requirements for obtaining a molecular replacement solution using a given model, and for decision making in fragment-based molecular replacement, single-atom molecular replacement, and likelihood-guided model pruning.