Predicting　the　accurate　stock　price　and　variation　trends　is　crucial　for　companies　and　individuals　before　purchasing　the　stock.　With　the　algorithm＇s　accurate　predictions,　it　could　offer　precious　suggestions　for　the　buyers　and　help　them　to　choose　the　best　stock　in　the　market　to　avoid　potential　risks.　This　paper　recorded　the　experiment　carried　out　for　predicting　the　trends　of　Tesla　from　2017　to　2018　and　then　compared　the　result　with　actual　trends.　This　paper　also　compares　the　accuracy　of　different　algorithms,　including　linear　regression　and　KNN　(K-Nearest　Neighbors)　etc.　This　paper　aims　to　demonstrate　the　detailed　process　of　predicting　a　stock　in　the　stock　market　covering　from　acquiring　data,　washing　data　and　most　importantly　using　multiple　algorithms　to　analyze　the　data　and　generate　a　final　prediction.　©　2022　IEEE.