In this study, the time and costs associated with product development are predicted using manufacturing data. This study investigates the relationship between product development time and costs and production dates, and it creates models that may be applied to anticipate these factors. Statistical methods like regression analysis and machine learning algorithms are used in research procedures to collect and analyze production data. The findings show that product development durations and costs may be accurately predicted using production data, and that these forecasts are more precise than those made using more conventional techniques that rely on expert judgement and historical data. The report also explores how these conclusions will affect product development teams as well as managers and professionals working in risk analysis and project management. Production data assists businesses in better informed resource allocation and project planning, resulting in more productive and efficient production by more precisely calculating the time and costs associated with product creation. resulting in an enhanced product development process and company success.