Stock trading signal decision is an important approach for investors in financial investment. Most previous studies focus on the precise price prediction, but trading point decision is more practical than price prediction. This paper proposes a novel approach using Petri nets to discover the relationships between various technical indicators, and exploring the rules of trading points hidden in historical data. Experiment results show that stock trading point decision with proposed Petri nets model can make a considerable return in investment.