Therapy-induced neuroendocrine prostate cancer (NEPC), an extremely aggressive variant of castration-resistant prostate cancer (CRPC), is increasing in incidence with the widespread use of highly potent androgen receptor (AR)-pathway inhibitors (APIs) such as Enzalutamide (ENZ) and Abiraterone and arises via a reversible trans-differentiation process, referred to as neuroendocrine differentiation (NED). The molecular basis of NED is not completely understood leading to a lack of effective molecular markers for its diagnosis. Here, we demonstrate for the first time, that lineage switching to NE states is accompanied by key miRNA alterations including downregulation of miR-106a~363 cluster and upregulation of miR-301a and miR-375. To systematically investigate the key miRNAs alterations driving therapy-induced NED, we performed small RNA-NGS in a retrospective cohort of human metastatic CRPC clinical samples + PDX models with adenocarcinoma features (CRPC-adeno) vs those with neuroendocrine features (CRPC-NE). Further, with the application of machine learning algorithms to sequencing data, we trained a 'miRNA classifier' that could robustly classify 'CRPC-NE' from 'CRPC-Adeno' cases. The performance of classifier was validated in an additional cohort of mCRPC patients and publicly available PCa cohorts. Importantly, we demonstrate that miR-106a~363 cluster pleiotropically regulate cardinal nodal proteins instrumental in driving NEPC including Aurora Kinase A, N-Myc, E2F1 and STAT3. Our study has important clinical implications and transformative potential as our 'miRNA classifier' can be used as a molecular tool to stratify mCRPC patients into those with/without NED and guide treatment decisions. Further, we identify novel miRNA NED drivers that can be exploited for NEPC therapeutic targeting.