In today's rapidly evolving business landscape, the pace of change is driven by disruptive technologies and shifting consumer preferences. One model gaining significant traction, particularly in web services and software for product IT companies, is the Freemium pricing strategy. The Freemium model provides basic services for free while charging for additional premium features. Researching the Freemium business model is highly relevant as it presents opportunities for enterprises to attract users and monetize their product or service offerings. However, maximizing this model's effectiveness requires a deep understanding of user acquisition dynamics, preferences, and willingness to pay - factors that can be experimentally modeled using Python functionality. Goal of paper is to determine the optimal premium price point and factors influencing revenue under the Freemium model for IT companies using the Python programming language. We identified the optimal premium subscription price for maximizing IT company profits under the Freemium business model through Python simulation experiments. Our methods include optimization models (profit maximization in discrete Freemium models), simulation modeling (discrete pricing model), and graphical methods (interpreting economic metrics under premium user share impact) in Google Colab. In the paper a Freemium pricing model for premium customers was investigated, visualized, and experimentally generated using Python, aimed at maximizing the profits of IT companies through simulation modeling using Python. A discrete dynamic model was developed relating profit to the share of premium users. The optimal premium subscription price for maximizing IT company profits was determined in Python through simulation experiments in Colab Environment.