<p>The estimation of effort is a crucial steps in the software development process for establishing necessary resources, their quantity, and the project's duration. However, the accuracy and reliability of early estimates may be diminished if customer requirements change as the project progresses. This work aims to enhance effort estimate by providing a framework that estimates the project's effort. This framework estimates the project effort with a use-case point technique based on real-project repository data. The input values comprehend in data such as the project's domain, technical variables, environmental conditions, and information. The proposed framework calculates the project's duration by utilizing the input values. Developers and project managers may compare and anticipate the duration of future projects using the use case repository, a database maintained by the framework. Fuzzy logic predicts the time using fuzzy rules and a triangle membership function to improve accuracy and reliability. By comparing the results with well-known datasets, the estimation's accuracy is shown. Using a machine learning system and the Gaussian Process Regression approach, regression analysis is done to predict how long the project will take. The widely accessible Deshranais dataset is used to validate the training and testing data that was gathered from friends, classmates, and other software companies. In the end, reports and comparative analysis are generated using a business intelligence tool based on different properties in the repository data.</p>