This study proposes an advanced inventory model that addresses the challenges associated with deteriorating items in a fuzzy environment. The model integrates joint pricing and inventory control while considering partial backlogging and time- and price-dependent demand. The deteriorating items are characterized by their decreasing value over time, and the fuzzy environment accounts for the inherent uncertainty in the real business world. The model recognizes the interdependence of pricing and inventory decisions, acknowledging that pricing strategies can influence inventory levels and vice versa. The model incorporates a partial backlog to accommodate customers who are prepared to wait for out-of-stock items, thereby minimizing lost sales and enhancing customer satisfaction. The model's application has the potential to enhance operational efficiency, improve customer satisfaction, and maximize profitability for businesses operating in diverse industries. A trapezoidal fuzzy number is assigned to the cost parameter and defuzzyfy by applying the graded mean representation method. A numerical example has been considered to illustrate the model, and the significant features of the results are discussed. Finally, based on these examples, sensitivity analyses have been studied by taking one parameter at a time and keeping the other parameters the same.