Depressive disorders are among the leading causes of global disease burden, but there has been limited progress in understanding the causes and treatments for these disorders. In this Perspective, we suggest that such progress crucially depends on our ability to measure depression. We review the many problems with depression measurement, including limited evidence of validity and reliability. These issues raise grave concerns about common uses of depression measures, such as diagnosis or tracking treatment progress. We argue that shortcomings arise because depression measurement rests on shaky methodological and theoretical foundations. Moving forward, we need to break with the field's tradition that has, for decades, divorced theories about depression from how we measure it. Instead, we suggest that epistemic iteration, an iterative exchange between theory and measurement, provides a crucial avenue for depression measurement to progress.