We introduce a novel machine learning framework for estimating the Bayesian posteriors of morphological parameters arbitrarily large numbers galaxies. The Galaxy Morphology Posterior Estimation Network (GaMPEN) estimates values and uncertainties galaxy's bulge-to-total light ratio ($L_B/L_T$), effective radius ($R_e$), flux ($F$). To estimate posteriors, GaMPEN uses Monte Carlo Dropout techniqu...