This thesis is focusing on market analysis and the application of machine learning techniques to predict movie genres of a specific streaming service. The primary objective is constructing predictive classification models that can accurately forecast movie genres based on their given descriptions. These models are then evaluated using various metrics to assess their performance and understand their limitations. The ultimate aim of this study is to gain a deeper understanding of how these predictive models function, providing valuable insights for future reference and applications. Additionally, the insights gained from this study could potentially be applied to other domains within the entertainment industry.