Random name generator
Make up realistic names for a story, a game character, test data or a placeholder. Pick the kind of name and press Generate. Tap a name to copy it.
Runs in your browser. Nothing is sent to a server.
Where the names come from
First names are drawn from 142 female and 155 male names that are among the most common given to babies in the United States in recent decades, based on Social Security baby name records. Last names come from 164 of the most common surnames in the US Census, which mix English, Spanish, Vietnamese, Korean, Chinese and Indian family names, much like a real class list or phone book.
Each batch has no repeats. The names are picked with your browser's cryptographic random generator, so every combination has the same chance.
How many different names each setting can make
| Setting | Different results | Good for |
|---|---|---|
| Full name, any | 48,544 | Test data, big rosters |
| Full name, male | 25,420 | A cast split by gender |
| Full name, female | 23,288 | A cast split by gender |
| First name only, any | 296 | Usernames, word problems |
| Last name only | 164 | Family or company names |
How these add up: 155 male first names × 164 surnames = 25,420, and 142 × 164 = 23,288 for female names. One name, Parker, is on both first-name lists, so "any" has 296 different first names rather than 297, and 296 × 164 = 48,544 full names. You can ask for up to 100 at a time. With "Last name only" that is more than half of all the surnames in one go, which is why a big batch of surnames can look familiar.
Tap any name in the result to copy just that one, or use Copy result for the whole list. Draw from these sends the batch to the name picker, which is handy for a practice raffle or for making sample teams.
What people use it for
- Writing and games: name side characters, NPCs or a cast for a short story without stopping to think.
- Test data: fill a form, a demo account or a spreadsheet with names that look real but belong to nobody in particular.
- Teaching: make sample rosters, word problems ("Mia buys 3 apples…") or role-play cards.
- Placeholders: mockups and slides read better with real-looking names than "User 1, User 2".
Tips for good fake names
| You need | Try |
|---|---|
| A cast where names don't sound alike | Generate 20, keep the ones that start with different letters |
| Usernames or email test data | First only, then add a number: olivia42, mateo.rivera |
| A balanced sample | Run Female and Male separately with the same count |
| A single surname for a family | Last only, How many = 1 |
Generated names can match real people, since they are common names. Don't use them to stand in for a real person, and for anything published, check the full name isn't a well-known figure.
Questions
Are these real people?
No. First and last names are combined at random, so any match with a real person is a coincidence. Because the names are common, matches do happen, the same way two strangers can share a name.
Can the same name come up twice?
Not in one batch: each list has no repeats. Across batches it can, since every press starts fresh. Any one full name has about a 1 in 48,544 chance per pick, so a particular name you liked turns up in roughly one batch of 100 out of every 485.
How is this different from the name picker?
This page makes up new names. The name picker draws from names you paste in, for raffles, teams or turn order.