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Recently, organic–inorganic perovskites have manifested great capacity to enhance the performance of photovoltaic systems, owing to their impressive optical and electronic properties. In this simulation survey, we employed the Solar Cell Capacitance Simulator (SCAPS-1D) to numerically analyze the effect of different hole transport layers (HTLs) (Spiro, CIS, and CsSnI₃) and perovskite active layers (ALs) (FAPbI₃, MAPbI₃, and CsPbI₃) on the solar cells’ performance with an assumed configuration of FTO/SnO₂/AL/HTL/Au. The influence of layer thickness, doping density, and defect density was studied. Then, we trained a machine learning (ML) model to perform predictions on the performance metrics of the solar cells. According to the SCAPS results, CsSnI₃ (as HTL) with a thickness of 220 nm, a defect density of 5 × 10¹⁷ cm⁻³, and a doping density of 5 × 10¹⁹ cm⁻³ yielded the highest power conversion efficiency (PCE) of 23.90%. In addition, a 530 nm-FAPbI₃ AL with a bandgap energy of 1.51 eV and a defect density of 10¹⁴ cm⁻³ was more favorable than MAPbI₃ (1.55 eV) and CsPbI₃ (1.73 eV) to attain a PCE of >24%. ML predicted the performance matrices of the investigated solar cells with ~75% accuracy. Therefore, the FTO/SnO₂/FAPbI₃/CsSnI₃/Au structure would be suitable for experimental studies to fabricate high-performance photovoltaic devices.