This review is an argument in favor of better drug target identification. It presents the many merits and feasibilities of drug localization and target identification through the use of a suitable technique: receptor microautoradiography. Studies of drug targets and target bioavailability require methods with high resolution and sensitivity to gain information for understanding mechanisms of action, sound modeling, prediction of effects, and toxicity. For in vivo localization of drugs in tissues and cells, receptor microautoradiography was specifically designed to preserve both tissue structure and deposition of noncovalently bound diffusible compounds and to enable microscopic viewing, quantitative analysis, and characterization of target sites. This method and its applications are explained here. Pictorial and quantitative data are provided together with a discussion of identified targets that document the utility of receptor microautoradiography. For example, when applied to quantitative studies of vitamin D compounds, pharmacokinetic data of blood differed from those of target tissues and even among target tissues. Many of the target tissues discovered and characterized with receptor microautoradiography remained unrecognized with common ADME procedures, radioassay–HPLC, and whole-body autoradiography. For a visual overview of the multiple vitamin D targets, a drug homunculus has been composed. Such a drug or target homunculus may be created for any drug, dose, and time to aid in documenting and fingerprinting. Receptor microautoradiography also is a sensitive method. It can be used for the study of low-dose stimulatory actions of toxic substances to show relationships of receptor binding to dose-dependent reversal of effects, known as hormesis. In addition, a combination of autoradiography and immunocytochemistry with radiolabeled drug and antibodies to receptor or other cellular product permits further target characterization. In its own league, receptor microautoradiography provides unique information. Through greater detail and certainty, it can validate and complement less-sensitive approaches, decrease the failure rates of current ADMET predictions, and serve as a diagnostic tool and guide for biochemical, functional, and clinical follow-up in drug research and development.