Multi Attribute Decision Making (MADM) is vital for evaluating diverse criteria in real-world scenarios. With the rise of e-commerce, efficient delivery systems are essential, particularly in urban areas facing demand for sustainable logistics. Delivery lockers streamline last-mile deliveries, reduce traffic congestion, and minimize environmental impact. This study proposes a robust MADM model to optimize locker placement using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method with Einstein operators in a Pythagorean fuzzy context. Criteria such as proximity, accessibility, costs, security, and scalability are assessed. Expert judgments are aggregated via Einstein operators to enhance decision stability. The Pythagorean fuzzy TOPSIS approach ranks locations by closeness to the ideal solution. This model offers a scalable, reliable framework for optimizing locker placements, supporting operational efficiency and sustainability in urban areas.