Random Number Generator

Generate random integers or decimals in any range — instantly

Random Number Generator

Generate random numbers within a range

Random Number Generator

Set a min and max range

Formula
floor(random() x (max - min + 1)) + min

What is a Random Number Generator?

A Random Number Generator (RNG) is a tool that produces numbers unpredictably within a range you choose. You set a minimum value and a maximum value, and the tool generates a random number between them. This is useful for games, picking winners, making random selections, simulating outcomes, and testing software.

Random number generators are often used to avoid bias when choosing something. For example, you can randomly select a number to decide a turn order, generate random quiz questions, pick a raffle winner, or create random test data for programming and spreadsheets.

Generator Options

This tool lets you set a Min and Max value and generates a random integer within that range. More advanced RNG tools may also support:

  • Count-- how many random numbers to generate at once
  • Decimals-- generate decimal numbers instead of integers only
  • Unique numbers-- ensure no duplicates in the generated set

Most online RNG tools use a pseudo-random algorithm, which means the numbers are generated by a mathematical process that appears random. For everyday uses—like giveaways, classroom activities, games, and testing—this is more than sufficient.

How to Use This Random Number Generator

  1. Enter the minimum value (Min)-- the lowest number that can be generated
  2. Enter the maximum value (Max)-- the highest number that can be generated
  3. Click 'Calculate'-- to generate your random number
  4. Review the result-- a random integer within the specified range is displayed
  5. Generate again-- click Calculate again for a new random number each time

Tips:

  • Make sure Min is less than Max—the tool needs a valid range to generate from
  • If you enable unique numbers (on tools that support it), the count cannot exceed the size of the range (e.g., you cannot generate 20 unique integers from 1 to 10)
  • Results will change each time you generate -- this is expected for a random tool

Formulas

Random Integer (Inclusive Range)

A basic way to generate a random integer between Min and Max (inclusive):

Random Integer = ⌊Random(0,1) × (Max − Min + 1)⌋ + Min

Random(0,1) -- a random decimal from 0 up to (but not including) 1

⌊ ⌋ -- floor function (round down)

Random Decimal (Continuous Range)

For generating decimal values within a range:

Random Decimal = Random(0,1) × (Max − Min) + Min

No floor function needed for decimal results

A Note on Randomness

Most online tools produce pseudo-random numbers using algorithms. For typical use (games, classroom, random picks, test data), this is perfectly fine. If you need cryptographic security (passwords, encryption keys), use a security-focused generator.

Example Calculations

Example 1: One Random Integer from 1 to 10

Min: 1, Max: 10

Output: any whole number: 1, 2, 3, …, 10

Example result: 7 (your result will vary)

Example 2: Five Random Integers from 100 to 200

Min: 100, Max: 200, Count: 5

Possible output: 112, 198, 145, 160, 101 (results vary)

Example 3: Three Unique Integers from 1 to 5

Min: 1, Max: 5, Count: 3, Unique: ON

Possible output: 2, 5, 1 (no repeats)

Example 4: Random Decimal from 0 to 1

Min: 0, Max: 1, Decimals: ON

Possible output: 0.3729 (results vary)

Frequently Asked Questions

Are the numbers truly random?

Most online random number generators use pseudo-random algorithms, which produce results that look random for everyday purposes. For games, raffles, and testing, they are typically sufficient.

Why do I sometimes see repeated numbers?

If 'unique numbers' is off, repeats are allowed. Even with randomness, repeats can occur naturally—especially when the range is small.

What does 'unique numbers' mean?

It means the generator will not repeat the same number in the output set. This is useful for picking distinct winners or creating non-duplicated selections.

What happens if Min is greater than Max?

The input is invalid. The tool will require you to correct the values. Always ensure Min ≤ Max.

Can I use this for passwords or security keys?

For security-sensitive use, you should use a cryptographically secure generator (often labeled 'secure random' or 'crypto-safe'). A general RNG is best for non-security uses like games, simulations, and random picks.

Embed This Random Number Generator on Your Website

Want to add this random number generator to your website? Get a custom embed code that matches your site's design and keeps visitors engaged.

Responsive design
Custom styling
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Mobile optimized

What Is a Random Number Generator?

A random number generator (RNG) produces numbers that have no predictable pattern. Random numbers are used in games (dice rolls, card shuffles), statistical sampling, simulations (Monte Carlo methods), cryptography, and decision-making (picking a random winner). This tool generates pseudo-random numbers using your browser's built-in cryptographic random function, so results are unpredictable and unbiased for everyday use.

You can generate a single random integer in any range — for example, 1–6 for a dice roll simulation or 1–100 for a lottery pick. Need more? Generate multiple numbers at once, choose whether to allow repeats, or switch to decimal mode to get a random value between 0 and 1 for probability experiments and simulations.

How to Use the Random Number Generator

  1. Set the minimum and maximum values for your range (e.g., 1 and 100).
  2. Choose how many numbers to generate in one click.
  3. Select whether to allow duplicate values in the results.
  4. Click Generate and copy your results instantly.

Formulas and Methods

Random integer in [min, max]: floor(Math.random() × (max − min + 1)) + min Random decimal in [0, 1): Math.random() Random decimal in [min, max): Math.random() × (max − min) + min Cryptographically secure (browser): crypto.getRandomValues(array)

Math.random() is pseudo-random — perfectly fine for games and simulations, but NOT suitable for security-sensitive work like generating passwords or tokens. For those use cases, use crypto.getRandomValues(), which draws from the operating system's entropy pool.

Common Use Cases

Simulate a 6-sided die

Set the range to 1–6 and generate 1 number. Each click replicates a single fair die roll. Roll multiple times in one go by increasing the count.

Pick 5 lottery numbers

Set the range to 1–49, generate 5 numbers, and disable duplicates. You'll get five unique numbers just like a real lottery draw — no repeats guaranteed.

Random decimal for probability simulation

Set the range to 0–1 in decimal mode. The result is a uniformly distributed value between 0 and 1, useful for Monte Carlo simulations, probability experiments, and random sampling in statistics.

Frequently Asked Questions

What is the difference between true random and pseudo-random numbers?
True random numbers come from physical processes — radioactive decay, atmospheric noise, or thermal fluctuations — that are genuinely unpredictable. Pseudo-random number generators (PRNGs) use a deterministic algorithm seeded with a starting value; they produce sequences that look random but are fully reproducible if you know the seed. For most everyday uses (games, simulations, random selections), PRNGs are indistinguishable from true random. This tool uses crypto.getRandomValues() under the hood, which is seeded from OS-level entropy and is far stronger than Math.random().
Is this tool safe to use for generating passwords?
This generator is NOT designed for password generation. While it uses the browser's cryptographic API (crypto.getRandomValues), it outputs plain numbers — not the mix of letters, symbols, and digits that strong passwords require. For passwords, use a dedicated password manager or a tool specifically built for that purpose. Random numbers are great for games, decisions, and statistics, but security credentials need a different approach.
How do I use a random number generator for statistics?
In statistics, random numbers are used to draw random samples from a population, assign participants to experimental groups (randomization), and run simulations. To take a random sample: number each item in your population from 1 to N, then generate that many random integers in range 1–N (without repeats) to select your sample. This ensures every item has an equal chance of being chosen, eliminating selection bias.
What does 'seed' mean in a random number generator?
A seed is the starting value fed into a pseudo-random algorithm. The same seed always produces the exact same sequence of numbers. Seeds are useful in science and testing: you set a seed before a simulation so colleagues can reproduce your exact results. In games, seeds are used to generate identical procedural worlds (Minecraft maps, for example). This tool does not expose a seed control because it uses the OS entropy pool, which changes every time — giving you a fresh, unrepeatable sequence on each use.
How do I pick a random winner from a list?
Number each entry in your list starting from 1. Count the total number of entries — say there are 50. Set the range to 1–50, generate 1 number, and the result tells you which entry wins. For multiple winners without repeats, generate multiple numbers with duplicates disabled, then match the numbers to your list. This method is fair, transparent, and easy to verify.