Crowdfunding that is the combination word of crowdsourcing and funding makes people can start a business easily. Legislating JOBS act in US played a major role in removing restricted barriers of crowdfunding on public offerings of fence and private funds for small business. The growth speed of crowdfunding takes some beating. Through Kickstarter that is a popular crowdfunding platform and being considered the typical case of crowdfunding, 480 million dollars and more than half a billion dollars were invested in about 19 thousand and 22 projects for 2013 and 2014 respectively. But in spite of the rapid growth, the successful rate of projects at large is decreasing because of imprudent project launching. People just imagine a success story of some triumphant projects without any kind of preparedness when they launch a project. Up to now most of papers researched based on Kickstarter platform because it is the biggest crowdfunding site. But there is no research paper studying with the entire data yet. So, we gathered all the project's main pages in Kickstarter that are finished whether a project is funded or not from its launched date on 2009 to September, 2014. And we also collected all users' profile pages including initiators and backers. The goal of this research project is to analyze evolution of projects and users, investigate techniques and predict successfully funded projects and expected pledged funding levels, and providing intelligent search and discovery based on time series patterns of projects. To successfully achieve the goal, we propose to analyze all projects and users in Kickstarter toward understanding evolution of them over time and thus develop statistical models to automatically predict successfully funded projects and expected funding level. We used as many features as possible such as features being obtainable from text (project main, reward and biography description). Our result will be very helpful for people especially a person preparing a crowdfunding project to fulfill a dream.