This paper proposes a conversion rate prediction method and a parameter reevaluation method based on Logistic curve (S-curve) to predict the spread of NCP (the Novel coronavirus pneumonia). According to the statistical data, we use the conversion rate prediction method to predict the spread of NCP. The prediction accuracy is quite high. By fitting the cumulative number of NCP sufferers with the logistic curve, the average estimation method of the limit number is proposed to predict the spread of NCP and the limit number of sufferers. This paper also assessing the effectiveness of prevention and control measures with the dynamic estimation of the infection probability of NCP. Based on the Markov property, the parameter reevaluation method proposed in this paper avoids over-fitting the theoretical curve and improves the accuracy of prediction. This research idea is not only suitable for Logistic curve regression, but also for other regression prediction problems.