diff --git a/tutorials/graph-theory/binary-search-tree.md b/tutorials/graph-theory/binary-search-tree.md
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--- a/tutorials/graph-theory/binary-search-tree.md
+++ b/tutorials/graph-theory/binary-search-tree.md
@@ -1,6 +1,6 @@
 ---
 title: 'Binary Search Tree'
-description: 'Coming Soon!'
+description: 'A binary tree where left child is less than or equal to the parent, while the right child is greater'
 draft: true
 keywords:
   - leetcode
@@ -9,4 +9,269 @@ keywords:
   - data structure
 ---
 
-Coming Soon
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+<TutorialAuthors names="@ChiragAgg5k"/>
+
+## Overview
+
+A **binary search trees (BST)** are basically [binary trees](./binary-tree.md) where each node's value is larger than all the nodes in that node's left subtree, and smaller than all the nodes in that node's right subtree. This property allows the [binary search algorithm](./../basic-topics/binary-search.md) to be applied to the tree, which is useful for fast lookup, insertion, and deletion of the nodes.
+
+## Implementation
+
+A BST can be implemented using a [binary tree](./binary-tree.md) with the following structure:
+
+```cpp
+struct TreeNode {
+  int val;
+  TreeNode * left;
+  TreeNode * right;
+  TreeNode(): val(0), left(nullptr), right(nullptr) {}
+  TreeNode(int x): val(x), left(nullptr), right(nullptr) {}
+  TreeNode(int x, TreeNode * left, TreeNode * right): val(x), left(left), right(right) {}
+};
+```
+
+## Operations
+
+### Insertion
+
+Inserting a node into a BST is similar to inserting a node into a [binary tree](./binary-tree.md), except that the node must be inserted in the correct position to maintain the BST property. The following is an example of inserting a node into a BST:
+
+```cpp
+TreeNode* insert(TreeNode* root, int key) {
+  if (root == NULL) {
+    return new TreeNode(key);
+  }
+  if (key < root->val) {
+    root->left = insert(root->left, key);
+  } else {
+    root->right = insert(root->right, key);
+  }
+
+  return root;
+}
+```
+
+### Deletion
+
+There are 4 cases to consider when deleting a node from a BST:
+
+1. The node has no children - the node can be deleted without any further processing.
+2. The node has only a left child - the node can be deleted and replaced with its left child.
+3. The node has only a right child - the node can be deleted and replaced with its right child.
+4. The node has both a left and right child - the node can be deleted and replaced with the *minimum node in its right subtree*.
+
+```cpp
+TreeNode* deleteNode(TreeNode* root, int key) {
+  if (root) {
+    if (key < root->val) {
+      root->left = deleteNode(root->left, key);
+    } else if (key > root->val) {
+      root->right = deleteNode(root->right, key);
+    }
+
+  } else {
+    if (!root->left && !root->right) {
+      return NULL;
+    }
+    if (!root->left || !root->right) {
+      return root->left ? root->left : root->right;
+    }
+
+    TreeNode* temp = root->left;
+
+    while (temp->right != NULL) {
+      temp = temp->right;
+    }
+
+    root->val = temp->val;
+    root->left = deleteNode(root->left, temp->val);
+  }
+
+  return root;
+}
+```
+
+
+### Searching
+
+Searching in a BST follows the same logic as in binary search, using the divide and conquer approach. The following is an implementation of searching in a BST:
+
+```cpp
+TreeNode* search(TreeNode* root, int key) {
+  if (root == NULL || root->val == key) {
+    return root;
+  }
+
+  if (key < root->val){
+    return search(root->left, key);
+  }
+
+  return search(root->right, key);
+}
+```
+
+## Balanced Binary Search Trees
+
+A binary search tree is said to be **balanced** if the height of the left and right subtrees of every node differ by at most 1. A balanced BST has applications in many algorithms, such as **AVL trees** and **red-black trees**.
+
+We can convert a binary tree into a balanced BST by first traversing the tree in inorder and storing the values in an array, and then constructing a balanced BST from the array. The following leetcode problem demonstrates this approach:
+
+[1382 - Balance a Binary Search Tree](https://leetcode.com/problems/balance-a-binary-search-tree/)
+
+> Given the root of a binary search tree, return a balanced binary search tree with the same node values. If there is more than one answer, return any of them.
+
+```cpp
+class Solution {
+ public:
+  void inorder(TreeNode* root, vector<int>& ans) {
+    if (root == NULL) return;
+
+    inorder(root->left, ans);
+    ans.push_back(root->val);
+    inorder(root->right, ans);
+  }
+
+  TreeNode* createBST(vector<int> ans, int start, int end) {
+    if (start > end) return NULL;
+
+    int mid = start + (end - start) / 2;
+    TreeNode* root = new TreeNode(ans[mid]);
+    root->left = createBST(ans, start, mid - 1);
+    root->right = createBST(ans, mid + 1, end);
+    return root;
+  }
+
+  TreeNode* balanceBST(TreeNode* root) {
+    vector<int> ans;
+    inorder(root, ans);  // Store the inorder traversal of the tree in an array
+
+    int start = 0, end = ans.size() - 1;
+    return createBST(ans, start, end);
+  }
+};
+```
+
+## Example #1: [0701 - Insert into a Binary Search Tree](https://leetcode.com/problems/insert-into-a-binary-search-tree/)
+
+> You are given the root node of a binary search tree (BST) and a value to insert into the tree. Return the root node of the BST after the insertion. It is guaranteed that the new value does not exist in the original BST.
+
+In this problem, we are asked to insert a node with a given key into a BST. To do so, first we need to find the correct position to insert the node and then insert it. The solution to this problem is as follows:
+
+```cpp
+class Solution {
+ public:
+  TreeNode* insertIntoBST(TreeNode* root, int key) {
+    // If root is NULL, insert the node at the root
+    if (root == NULL){
+      return new TreeNode(key);
+    }
+
+    // If key is less than root's value, recurse into the left subtree, else
+    // recurse into the right subtree
+    if (key < root->val){
+      root->left = insertIntoBST(root->left, key);
+    } else {
+      root->right = insertIntoBST(root->right, key);
+    }
+    return root;
+  }
+};
+```
+
+## Example #2: [0450 - Delete Node in a BST](https://leetcode.com/problems/delete-node-in-a-bst/)
+
+> Given a root node reference of a BST and a key, delete the node with the given key in the BST. Return the root node reference (possibly updated) of the BST.
+
+In this problem, we are asked to delete a node with a given key from a BST. Now its fairly easy to navigate to the node with the given key, but the problem is that we need to *maintain the BST property* after deleting the node. For this we can apply the logic of deletion in a BST, which is described above. The following is the complete solution to this problem:
+
+```cpp
+class Solution {
+ public:
+  TreeNode *deleteNode(TreeNode *root, int key) {
+    if (root) {
+      if (key < root->val) {
+        root->left = deleteNode(root->left, key);
+      } else if (key > root->val) {
+        root->right = deleteNode(root->right, key);
+      } else {
+        // If the node has no children, delete it directly
+        if (!root->left && !root->right) return NULL;
+
+        // If the node has only one child, delete it and replace it with its child
+        if (!root->left || !root->right) {
+          return root->left ? root->left : root->right;
+        }
+
+        // If the node has both a left and right child, replace it with the minimum
+        TreeNode *temp = root->left;
+        while (temp->right != NULL) {
+          temp = temp->right;
+        }
+
+        root->val = temp->val;
+        root->left = deleteNode(root->left, temp->val);
+      }
+    }
+    return root;
+  }
+};
+```
+
+## Example #3: [0700 - Search in a Binary Search Tree](https://leetcode.com/problems/search-in-a-binary-search-tree/)
+
+> Find the node in the BST that the node's value equals val and return the subtree rooted with that node. If such a node does not exist, return null.
+
+In this problem, we are asked to find a node with a given key in a BST. This can be done in an optimal way using the divide and conquer approach due to the BST property. The following is the complete solution to this problem:
+
+```cpp
+class Solution {
+ public:
+  TreeNode* searchBST(TreeNode* root, int key) {
+    // Either root is found or the key is not present in the BST
+    if (root == NULL || root->val == key){
+      return root;
+    }
+
+    // If key is less than root's value, recurse into the left subtree, else
+    if (key < root->val){
+      return searchBST(root->left, key);
+    }
+
+    // Recurse into the right subtree
+    return searchBST(root->right, key);
+  }
+};
+```
+
+## Complexity Analysis
+
+| Operation | Time Complexity | Space Complexity |
+| --------- | --------------- | ---------------- |
+| Insertion | O(n)            | O(n)             |
+| Deletion  | O(n)            | O(n)             |
+| Searching | O(n)            | O(n)             |
+
+where $n$ is the number of nodes in the BST.
+
+export const suggestedProblems = [
+  {
+    "problemName": "0098 - Validate Binary Search Tree",
+    "difficulty": "Medium",
+    "leetCodeLink": "https://leetcode.com/problems/validate-binary-search-tree/",
+    "solutionLink": "../../solutions/0000-0099/validate-binary-search-tree-medium"
+  },
+  {
+    "problemName": "0230 - Kth Smallest Element in a BST",
+    "difficulty": "Medium",
+    "leetCodeLink": "https://leetcode.com/problems/kth-smallest-element-in-a-bst/",
+    "solutionLink": "../../solutions/0200-0299/kth-smallest-element-in-a-bst-medium"
+  },
+  {
+    "problemName": "0703 - Kth Largest Element in a Stream",
+    "difficulty": "Easy",
+    "leetCodeLink": "https://leetcode.com/problems/kth-largest-element-in-a-stream/",
+    "solutionLink": "../../solutions/0700-0799/kth-largest-element-in-a-stream-easy"
+  },
+]
+
+<Table title="Suggested Problems" data={suggestedProblems} />
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