This paper is dealing with predictive modeling based on predictive analytics using computer application system and the usage of the prediction results for decision-making processes. Usually the prediction is based on the experience of decision makers, but the aim of this study is to explain and proof higher predictive efficiency when using predictive analytics based on machine learning as well as more accurate future-oriented business decisions. The marina industry in Croatia is used for this research because of its complexity and necessity to predict future events that influence company success with reliable accuracy. The information for decision-making were obtained from the customer database recorded manually over the past 30 years and according to data from December 2020. The optimized prediction by the vector machine and statistical theory based on the Bayes theorem is used to support more accurate prediction. The quantitative research was carried out using the SAP Predictive Analytics (SAP PA) computer application. The results of prediction models are a perfect basis for making future-oriented strategic and tactical decisions. This research proves that, with knowledge obtained from the results of prediction models it is possible to improve the identification of the target group among applicants and customers that contribute to company success. The research provides a theoretical and an empirical contribution in the usage of predictive analytics in the marina industry in Croatia.