R Saritha, Kamal Suthar, Sowmya, P Ganesh, Keerthan 03 09 The Personal Finance Tracker Analysis and Prediction system is designed to help individuals manage analyze and predict their personal financial activities in an organized manner Managing income expenses savings and financial goals manually can be difficult and may lead to poor spending decisions The proposed system provides a digital platform for recording financial transactions and analyzing spending patterns The system allows users to record income expenses savings loans and different spending categories such as food transportation shopping education bills and entertainment The collected financial data is stored and processed to generate useful summaries of the users financial activities Data analysis techniques are used to identify spending patterns frequently used categories monthly expenses and savings trends The system can use machine learning and statistical prediction techniques to forecast future expenses income and possible savings based on historical financial records The predicted information can help users understand their expected financial position and plan their future spending more effectively Visualizations such as pie charts bar charts line graphs and monthly summaries can make financial information easier to understand The proposed system can also provide budget monitoring and alerts when spending approaches or exceeds a predefined budget Users can compare their actual expenses with planned budgets and identify areas where unnecessary spending can be reduced Overall the Personal Finance Tracker Analysis and Prediction system provides a convenient and intelligent approach to personal financial management By combining transaction tracking data analysis visualization budgeting and prediction the system can help users make better financial decisions improve saving habits and achieve their financial goals Copyright (c) Journal of Science Engineering Technology and Management Science. All rights reserved 2026