This master thesis investigates the Black-Litterman Model through diverse mathematical perspectives, aiming to provide the reader with a comprehensive understanding of the model’s background and the functioning of its components. The analysis delves into the proof of the Black-Litterman formula, offering insights from various mathematical angles to enhance the reader’s grasp of the model’s intricacies. Emphasizing its parameter-rich structure, this study demonstrates how the model effectively addresses the diverse needs and sophisticated requirements of investors. Incorporating private views into the model, enhances portfolio implied returns, contributing to tailored investment solutions. The research derives the Black–Litterman Model, elucidating its impact on expected returns and portfolio optimization. Additionally, insights are provided by juxtaposing the model with the Capital Asset Pricing Model and Arbitrage Pricing Theory, broadening the scope of asset allocation strategies. Practically, the model is implemented on Exchange-Traded Funds (ETFs) across various markets, evaluating results alongside Mean-Variance Optimization with graphical analysis.