The　coastal　developments　in　the　Middle　East　put　low　priority　on　tsunami　risk　assessment　due　to　the　rare　occurrence　and　absence　of　genuine　tsunami　track　records　on　the　coastline　in　the　past.　Tsunami-vulnerable　coasts,　including　the　east　coast　of　the　UAE,　need　to　prepare　for,　and　pay　attention　to,　the　impact　of　future　tsunamis　due　to　increased　earthquake　activity　in　the　region.　This　study　investigated　the　tsunami　characteristics　of　the　nearshore　from　hypothetical　tsunami　conditions　by　applications　of　numerical　modeling　and　Artificial　Neural　Network　(ANN)　methods.　The　modeling　results　showed　that　the　maximum　tsunami　depth　at　the　shore　was　highest　in　Khor　Fakkan　and　Mirbih　for　the　given　tsunami　boundary　conditions,　while　the　tsunami　withdrawal　was　greater　on　the　southern　bathymetry　compared　to　that　on　the　northern　bathymetry　when　the　tsunami　period　increased.　ANN　results　confirmed　that　the　still　sea　depth　and　seabed　slope　were　more　important　than　the　tsunami　period　when　predicting　the　maximum　tsunami　depth　at　the　shore.　©　2025　by　the　authors.