diff --git a/pydatastructs/linear_data_structures/algorithms.py b/pydatastructs/linear_data_structures/algorithms.py
index 792bce855..2f0d69724 100644
--- a/pydatastructs/linear_data_structures/algorithms.py
+++ b/pydatastructs/linear_data_structures/algorithms.py
@@ -30,7 +30,8 @@
     'jump_search',
     'selection_sort',
     'insertion_sort',
-    'intro_sort'
+    'intro_sort',
+    'radix_sort'
 ]
 
 def _merge(array, sl, el, sr, er, end, comp):
@@ -1843,6 +1844,111 @@ def partition(array, lower, upper):
     elif maxdepth == 0:
         heapsort(array, start=lower, end=upper)
         return array
+
+def radix_sort(array: Array, **kwargs) -> Array:
+    """
+    Performs radix sort on the given array of non-negative integers.
+    Uses counting sort as a subroutine to sort by each digit position.
+
+    Parameters
+    ==========
+
+    array: Array
+        The array which is to be sorted. Must contain only non-negative integers.
+    start: int
+        The starting index of the portion
+        which is to be sorted.
+        Optional, by default 0
+    end: int
+        The ending index of the portion which
+        is to be sorted.
+        Optional, by default the index
+        of the last position filled.
+    backend: pydatastructs.Backend
+        The backend to be used.
+        Optional, by default, the best available
+        backend is used.
+
+    Returns
+    =======
+
+    output: Array
+        The sorted array.
+
+    Examples
+    ========
+
+    >>> from pydatastructs import OneDimensionalArray, radix_sort
+    >>> arr = OneDimensionalArray(int,[170, 45, 75, 90, 802, 24, 2, 66])
+    >>> out = radix_sort(arr)
+    >>> str(out)
+    '[2, 24, 45, 66, 75, 90, 170, 802]'
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Radix_sort
+
+    Note
+    ====
+
+    This implementation:
+    1. Only works with non-negative integers
+    2. Uses LSD (Least Significant Digit) radix sort
+    3. Uses base-10 digits
+    """
+    raise_if_backend_is_not_python(
+        radix_sort, kwargs.get('backend', Backend.PYTHON))
+    
+    # Find maximum number to know number of digits
+    max_val = 0
+    start = kwargs.get('start', 0)
+    end = kwargs.get('end', len(array) - 1)
+    
+    for i in range(start, end + 1):
+        if array[i] is not None and array[i] > max_val:
+            max_val = array[i]
+    
+    # Do counting sort for every digit
+    exp = 1
+    while max_val // exp > 0:
+        # Create output array with same type as input
+        output = type(array)(array._dtype, [array[i] for i in range(len(array))])
+        if _check_type(output, DynamicArray):
+            output._modify(force=True)
+        
+        # Store count of occurrences
+        count = [0] * 10
+        
+        # Count occurrences of current digit
+        for i in range(start, end + 1):
+            if array[i] is not None:
+                idx = (array[i] // exp) % 10
+                count[idx] += 1
+        
+        # Change count[i] to position of digit in output
+        for i in range(1, 10):
+            count[i] += count[i - 1]
+        
+        # Build output array
+        i = end
+        while i >= start:
+            if array[i] is not None:
+                idx = (array[i] // exp) % 10
+                output[start + count[idx] - 1] = array[i]
+                count[idx] -= 1
+            i -= 1
+        
+        # Copy output array to array
+        for i in range(start, end + 1):
+            array[i] = output[i]
+        
+        exp *= 10
+    
+    if _check_type(array, (DynamicArray, _arrays.DynamicOneDimensionalArray)):
+        array._modify(True)
+    
+    return array
     else:
         p = partition(array, lower, upper)
 
diff --git a/pydatastructs/linear_data_structures/tests/test_algorithms.py b/pydatastructs/linear_data_structures/tests/test_algorithms.py
index 46609544b..836a58020 100644
--- a/pydatastructs/linear_data_structures/tests/test_algorithms.py
+++ b/pydatastructs/linear_data_structures/tests/test_algorithms.py
@@ -5,7 +5,7 @@
     cocktail_shaker_sort, quick_sort, longest_common_subsequence, is_ordered,
     upper_bound, lower_bound, longest_increasing_subsequence, next_permutation,
     prev_permutation, bubble_sort, linear_search, binary_search, jump_search,
-    selection_sort, insertion_sort, intro_sort, Backend)
+    selection_sort, insertion_sort, intro_sort, Backend, radix_sort)
 
 from pydatastructs.utils.raises_util import raises
 import random
@@ -414,3 +414,45 @@ def test_binary_search():
 def test_jump_search():
     _test_common_search(jump_search)
     _test_common_search(jump_search, backend=Backend.CPP)
+
+def test_radix_sort():
+    random.seed(1000)
+
+    # Test with DynamicOneDimensionalArray
+    n = random.randint(10, 20)
+    arr = DynamicOneDimensionalArray(int, 0)
+    for _ in range(n):
+        arr.append(random.randint(1, 1000))
+    for _ in range(n//3):
+        arr.delete(random.randint(0, n//2))
+
+    # Test full array sort
+    expected_arr = [102, 134, 228, 247, 362, 373, 448,
+                   480, 548, 686, 688, 696, 779]
+    assert radix_sort(arr)._data == expected_arr
+
+    # Test with OneDimensionalArray
+    arr = OneDimensionalArray(int, [170, 45, 75, 90, 802, 24, 2, 66])
+    expected_arr = [2, 24, 45, 66, 75, 90, 170, 802]
+    out = radix_sort(arr)
+    assert [out[i] for i in range(len(out))] == expected_arr
+
+    # Test partial sort with start/end
+    arr = OneDimensionalArray(int, [170, 45, 75, 90, 802, 24, 2, 66])
+    out = radix_sort(arr, start=2, end=5)
+    expected_arr = [170, 45, 75, 90, 802, 24, 2, 66]
+    assert [out[i] for i in range(len(out))] == expected_arr
+
+    # Test with None values
+    arr = DynamicOneDimensionalArray(int, 0)
+    arr.append(45)
+    arr.append(None)
+    arr.append(12)
+    arr.append(None)
+    arr.append(89)
+    out = radix_sort(arr)
+    assert out[0] == 12
+    assert out[1] == 45
+    assert out[2] == 89
+    assert out[3] is None
+    assert out[4] is None