Purpose of Review: ‘Target bias’ is the difference between an estimate of association from a study sample and the causal effect in the target population of interest. It is the sum of internal and external bias. Given the extensive literature on internal validity, here, we review threats and methods to improve external validity. Recent Findings: External bias may arise when the distribution of modifiers of the effect of treatment differs between the study sample and the target population. Methods including those based on modeling the outcome, modeling sample membership, and doubly robust methods are available, assuming data on the target population is available. Summary: The relevance of information for making policy decisions is dependent on both the actions that were studied and the sample in which they were evaluated. Combining methods for addressing internal and external validity can improve the policy relevance of study results.