In terms of environmental impacts and cost considerations, the use of green additives particularly from plant origin have been found as a viable alternative approach to synthetic organic inhibitors in combatting the menace of corrosion. However, owing to the composition matrix complexity of plant extracts, efforts are seldom made to engage their isolated constituents for corrosion inhibition; hence their optimal utilization is hindered. In this research, corrosion inhibition properties of the rhizomes of Alpinia galanga and its constituents were investigated experimentally and theoretically on mild steel in hydrochloric acid solution using weight loss and electrochemical methods, and surface characterization techniques namely attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR), scanning electron microscopy (SEM), field emission scanning electron microscopy (FESEM) and energy dispersive X-ray spectroscopy (EDX). Explorations using response surface methodology (RSM) as the optimization tool and quantitative structure-activity relationship (QSAR) modelling of the plant’s major phenylpropanoids were carried out. At room temperature, efficiencies were highest at the uppermost concentrations of all the inhibitors in the following order: hexane extract (90.2%), essential oils (87.9%), and methanol extract (74.2%) while for the phenylpropanoid constituents; 1'-acetoxychavicol acetate (84.6%), methyl eugenol (83.6%), eugenol acetate (82.1%), eugenol (76.3%) and p-hydroxycinnamic acid (30.4%). Optimal efficiencies of 90.3% and 91.17% were attained for hexane extract and essential oil components, respectively, at optimized concentration, temperature, and time. Investigations revealed that mixed mode interactions for all the inhibitors and their effectiveness were supported by the surface characterization techniques. Inhibition efficiencies decreased with increasing temperature for all inhibitors except for the essential oil fraction which increased steadily. The Langmuir isotherm model showed the best fit, giving negative values of adsorption energies with thermodynamics and kinetics parameters supporting the principles of electrostatic interaction. The structural requirements of the phenylpropanoids for effective inhibition were clarified while electrostatic interaction-related descriptors were selected by penalization methods in the constructed QSAR models