The objective was to develop a model to a priori identify the most suitable depot technology for a candidate based upon its therapeutic index (TI), pharmacokinetics (PK), and physical chemical properties. A depot map of release rates needed to achieve target PK in TI against release rates predicted based on intrinsic dissolution rate (IDR) and particle size (PS) clearly identified three zones: (a) products and candidates around the line of identity for which suspension is the appropriate depot technology, (b) area to the right of line of identity in which depot candidates would require a controlled release technology such as PLGA microspheres since in vivo release rate needed for PK in TI is significantly lower than predicted based on IDR and PS, and (c) area to the left of the line of identity where IDR is not sufficient to achieve target in vivo release rate for PK in TI and hence enhanced dissolution is needed such as with nanoparticles. Dose-solubility technology map of approved depot products and candidates showed clusters of products around a depot technology such as suspensions and microspheres, for drugs with high dose/low solubility and low dose/high solubility compounds, respectively. Novel PK-based computational tool showed how all combinations of depot doses and release rate constants for a candidate can be calculated to achieve plasma levels within the TI bounded by minimum effective and minimum toxic concentrations (MEC and MTC). The PK predictions for several drugs such as estradiol, risperidone, medroxyprogesterone acetate (MPA), and ziprasidone showed how these predictions can guide scientists to target specific depot doses and release rates into the depot formulation. In parallel, IDR of depot compounds clearly showed differentiation of compounds by successful depot technologies to achieve target dose and duration. For drugs with IDR between 0.1 and 1 mg/h/cm², aqueous suspension has successfully delivered depot PK profile, while for candidates with IDRs greater than 1 mg/h/cm², controlled release technology such as microsphere or in situ gel was required. The framework, prediction tools, and depot map will reduce the need for semi-empirical formulation work and preclinical studies to design depot formulations.