Metabolic dysfunction-associated steatohepatitis (MASH) is a progressive liver disease characterized by chronic inflammation and fibrosis, for which effective therapies remain limited. Given the multifactorial nature of MASH, therapeutic approaches capable of modulating complex regulatory networks are required. To identify fibrosis-relevant targets and therapeutic microRNAs (miRNAs), we established an integrative workflow combining cellular models, quantitative proteomics and bioinformatic analyses. Proteomic profiling was performed in LX-2 cells, an immortalized human hepatic stellate cell (HSC) line, activated with transforming growth factor β1 (TGF-β1) to model a profibrotic phenotype. Proteins upregulated upon activation were analyzed using two complementary miRNA target prediction strategies: experimentally validated miRNA–target interactions curated in miRTarBase and computational predictions generated using the miRNA binding sites (MBS) tool. Among the identified candidates, the collagen-modifying enzyme prolyl 4-hydroxylase subunit alpha 2 (P4HA2) was selected for proof-of-concept validation. Functional screening of five miRNA mimics predicted to target P4HA2 identified miR-9-5p as the most effective candidate, capable of reducing P4HA2 protein levels and suppressing key profibrotic markers. Antifibrotic activity was further validated in HepG2/LX-2 co-culture liver spheroids, where collagen modulation was confined to the HSC-like cell compartment. Together, these data identify P4HA2 as a functionally relevant therapeutic target in activated HSCs and demonstrate the value of computationally guided miRNA prioritization for antifibrotic therapy development in MASH.