Introduction This study aimed to assess quantitative factors associated with treatment response and macular neovascularization (MNV) onset in central serous chorioretinopathy (CSC) through an artificial intelligence-based approach. Methods The study was designed as an interventional, prospective case series with a planned follow-up of 36 months. We included only eyes demonstrating the first episode of CSC. All the patients underwent eplerenone or photodynamic therapy (PDT) treatment. Eyes developing MNV underwent anti-VEGF injections. We developed an artificial intelligence-based model to assess predictive quantitative structural optical coherence tomography (OCT) factors related to treatment response and onset of MNV. Main outcome measures were best-correct visual acuity (BCVA), central macular thickness (CMT), retinal thickness (RT), retinal pigment epithelium (RPE) thickness, choroidal thickness, Sattler’s layer thickness (SLT), Haller’s layer thickness, retinal and choroidal hyperreflective foci (HF), and MNV. Results We included 96 naïve CSC eyes (96 patients). Baseline BCVA was 0.18 ± 0.25 logMAR, which increased to 0.16 ± 0.27 logMAR after 3 years ( p  > 0.05). Baseline CMT was 337 ± 126 µm, which improved to 229 ± 40 µm after 3 years ( p  < 0.01). We observed good response to eplerenone in 40/78 (51%) eyes, whereas 38/78 (49%) eyes underwent PDT. The artificial intelligence model showed choroidal HF and age as determining factors of good response to eplerenone or PDT. RPE thickness < 36 µm, RT < 300 µm, and SLT < 50 µm increased probability of 50% of having MNV. Conclusions CSC response to eplerenone or PDT is influenced by choroidal HF and patient age. RPE and SLT represent relevant factors for onset of MNV.