A method to predict the risk of lung cancer is proposed, based on two feature selection algorithms: Fisherand ReliefF, and BP Neural Networks. An appropriate quantity of risk factors was chosen for lung cancer riskprediction. The process featured two steps, firstly choosing the risk factors by combining two feature selectionalgorithms, then providing the predictive value by neural network. Based on the method framework, an algorithmLCRP (lung cancer risk prediction) is presented, to reduce the amount of risk factors collected in practicalapplications. The proposed method is suitable for health monitoring and self-testing. Experiments showed itcan actually provide satisfactory accuracy under low dimensions of risk factors.