This　paper　presents　a　classification　method　for　earthquake　ground　motion　records　utilizing　the　results　of　K-means　cluster　analysis.　The　moment　magnitude　and　Joyner-Boore　distance　are　utilized　as　the　primary　parameters　for　clustering　the　earthquake　ground　motion　records.　The　classification　boundaries　are　established　through　an　examination　of　moment　magnitude　ranges,　Joyner-Boore　distance　ranges,　and　spectral　characteristics　within　each　cluster.　In　this　study,　a　comprehensive　dataset　comprising　7627　horizontal　earthquake　acceleration　records　was　meticulously　curated　for　analysis.　The　data　were　subjected　to　separate　clustering　and　grouping　procedures,　allowing　for　insightful　comparisons　between　the　resultant　clusters.　Significant　disparities　in　spectral　characteristics　across　the　classification　groups　were　demonstrated.　These　differences　become　particularly　pronounced　when　a　moment　magnitude　threshold　of　6　and　a　Joyner-Boore　distance　threshold　of　140　km　are　employed　to　categorize　the　ground　motion　records.　The　approach　underscores　the　substantial　impact　of　classification　based　on　earthquake　ground　motion　spectral　characteristics,　while　also　mitigating　the　potential　instabilities　inherent　in　cluster　analysis　results.　A　refined　and　quantitatively　robust　framework　for　understanding　and　categorizing　earthquake　ground　motions　is　provided,　offering　valuable　insights　for　seismic　data　analysis　and　contributing　to　more　accurate　and　reliable　assessments　of　seismic　activity.