Perovskite solar cells (PSCs) have recently witnessed significant progress, reaching unprecedented efficiencies. However, improving material systems and processes remains a complex, multi-step task, often approached through trial-and-error. A crucial challenge for the commercialization of this technology is selecting solvents for depositing the perovskite active layers, for which there is currently no established methodology. Consequently, perovskites are ubiquitously processed using highly toxic solvents such as N,N-dimethylformamide (DMF), with a profound negative impact on the device's environmental footprint and severe concerns for workers’ safety when produced on scale. This study presents a predictive semi-empirical methodology for solvent selection for perovskite layer deposition. This approach combines Hansen solubility parameters (HSPs) with density functional theory (DFT) to identify and evaluate potential greener replacements for DMF in lead iodide-based perovskite solar cells. To demonstrate the approach's validity, five previously unexplored green solvents were selected and used to produce PSCs. Passivation-free inverted architecture devices fabricated from these green solvents showed performance comparable to devices processed using DMF, with one green solvent (IAAc) showing a modest statistical improvement. These results validate the method's predictive capability and represent a significant advance towards developing environmentally friendly processing routes for commercializing PSCs.