Aberrations in cyclic adenosine monophosphate (cAMP) signaling cascade has been linked to the allergic responses that associate with the risks of stroke or cardiovascular diseases. Phosphodiesterase 4D (PDE4D) has been shown to be highly involved in cAMP regulation and is hence implied to be a potential drug target in stroke prevention. To identify potential PDE4D inhibitors from traditional Chinese medicine (TCM), we employed machine learning modeling techniques to screen a comprehensive TCM database. The multiple linear regression (MLR) and support vector machine (SVM) models constructed have correlation coefficients of 0.8234 and 0.7854 respectively. Three candidates from the ginger family were identified based on the prediction models. Molecular dynamics simulation further validated the binding stabilities of each candidate in comparison to the control inhibitor L-454560. The intermolecular distances suggested that the candidates could hinder PDE4D from binding to cAMP. Furthermore, the HypoGen validation suggested that top2, top3, and the control L-454560 mapped with the predicted pharmacophores. The results suggested that the 3 compounds identified from the ginger family were capable in inhibiting cAMP binding and hydrolysis by PDE4D. We further identified and characterized the ligand binding properties that are associated with the inhibition of PDE4D.