Galaxy Zoo is a crowdsourced astronomy project which invites people to assist in the morphological classification of large numbers of galaxies. It is an example of citizen science as it enlists the help of members of the public to help in scientific research.

There have been 15 versions as of July 2017. Galaxy Zoo is part of the Zooniverse, a group of citizen science projects. An outcome of the project is to better determine the different aspects of objects and to separate them into classifications.

A key factor leading to the creation of the project was the problem of what has been referred to as data deluge, where research produces vast sets of information to the extent that research teams are not able to analyse and process much of it. Kevin Schawinski, previously an astrophysicist at Oxford University and co-founder of Galaxy Zoo, described the problem that led to Galaxy Zoo's creation when he was set the task of classifying the morphology of more than 900,000 galaxies by eye that had been imaged by the Sloan Digital Sky Survey at the Apache Point Observatory in New Mexico, USA. "I classified 50,000 galaxies myself in a week, it was mind-numbing." Chris Lintott, a co-founder of the project and a professor of astrophysics at the University of Oxford, stated: "In many parts of science, we're not constrained by what data we can get, we're constrained by what we can do with the data we have. Citizen science is a very powerful way of solving that problem."

The Galaxy Zoo concept was inspired by others such as Stardust@home, where the public was asked by NASA to search images obtained from a mission to a comet for interstellar dust impacts. Unlike earlier internet-based citizen science projects such as SETI@home, which used spare computer processing power to analyse data (also known as distributed or volunteer computing), Stardust@home involved the active participation of human volunteers to complete the research task. In August 2014, the Stardust team reported the discovery of first potential interstellar space particles after citizen scientists had looked through more than a million images.

In 2007, when Galaxy Zoo first started, the science team hoped that 20–30,000 people would take part in classifying the 900,000 galaxies that made up the sample. It had been estimated that a perfect graduate student working 24 hours a day 7 days a week would take 3–5 years to classify all the galaxies in the sample once. However, in the first Galaxy Zoo, more than 40 million classifications were made in approximately 175 days by more than 100,000 volunteers, providing an average of 38 classifications per galaxy.

Chris Lintott commented that: "One advantage is that you get to see parts of space that have never been seen before. These images were taken by a robotic telescope and processed automatically, so the odds are that when you log on, that first galaxy you see will be one that no human has seen before." This was confirmed by Kevin Schawinski: "Most of these galaxies have been photographed by a robotic telescope, and then processed by computer. So this is the first time they will have been seen by human eyes.".

Galaxy Zoo recruited volunteers to help with the largest galaxy census ever carried out. Opening the project to the general public saved the professional astronomers the task of studying all the galaxies themselves, resulting in classification of a large number of galaxies undertaken in a shorter time than what smaller research teams would be able to do, classifying 900,000 galaxies in months rather than years if done by smaller research teams. Computer programs had been unable to reliably classify galaxies: several groups had attempted to develop image-analysis programs. Kevin Schawinski stated: "The human brain is actually much better than a computer at these pattern recognition tasks." However, volunteers astonished the project's organizers by classifying the entire catalog years ahead of schedule. An online forum was later set up two weeks after the initial start, partially due to a large volume of emails being sent around, to the point that it was troublesome for those receiving them to process and respond to them. This led volunteers to point out anomalies that on closer inspection have turned out to be new astronomical objects such as 'Hanny's Voorwerp' and 'the Green Pea galaxies'. "I'm incredibly impressed by what they've managed to achieve," says University of Oxford astronomer Roger Davies, former president of the Royal Astronomical Society."They've made it possible to do things with a huge survey."

The Galaxy Zoo forum became a hotbed for the discussion of the SDSS images and more general science questions. Its 'global moderator', volunteer communuity manager and UK astronomy enthusiast Alice Sheppard, said of it: "I don't quite know what it is, but Galaxy Zoo does something to people. The contributions, both creative and academic, that people have made to the forum are as stunning as the sight of any spiral, and never fail to move me." Author Michael Nielsen wrote in his book Reinventing Discovery: "But Galaxy Zoo can go beyond computers, because it can also apply human intelligence in the analysis, the kind of intelligence that recognizes that Hanny's Voorwerp or a Pea galaxy is out of the ordinary, and deserves further investigation. Galaxy Zoo is thus a hybrid, able to do deep analyses of large data sets that are impossible in any other way." A community feeling was also created. Roger Davies stated: "The community of Galaxy Zoo gives them the opportunity to participate that they're looking for." This community became known as the 'Zooites'. Aida Berges, a homemaker living in Puerto Rico who has classified hundreds of thousands of galaxies, stated: "Every galaxy has a story to tell. They are beautiful, mysterious, and show how amazing our universe is. It was love at first sight when I started in Galaxy Zoo ... It is a magical place, and it feels like coming home at last." The Galaxy Zoo Forum became a read-only archive in July 2014. After seven years online and over 650,000 posts, it continues to generate science.