diff --git a/docs/dsa/binary_search/binary-search.md b/docs/dsa/binary_search/binary-search.md
index 9988b5705..fbc27804e 100644
--- a/docs/dsa/binary_search/binary-search.md
+++ b/docs/dsa/binary_search/binary-search.md
@@ -4,4 +4,59 @@ title: Binary Search
 sidebar_label: Binary Search
 description: "In this blog post, we'll dive into the binary search algorithm, a fundamental technique in computer science for efficiently finding an element in a sorted array."
 tags: [dsa, algorithms, binary search]
----
\ No newline at end of file
+---
+
+
+## Introduction
+Binary search is a searching algorithm, used to search for an element in an array. It follows a unique approach which reduces the time complexity as compared to linear search. However, to use binary search, the array must be sorted. 
+
+## Implementation
+
+Let us see how to implement binary search in Java:
+
+```java
+        //let element to be found=target
+		int low=0;
+		int high=n-1; //where n is the length of the sorted array
+        int mid; //represents the mid index of the array
+
+        int flag=0; //element not yet found 
+
+		while(low<=high) {
+
+			mid=(low + high)/2;
+			if(arr[mid]==target) {
+				flag=1; //element found
+				System.out.println("Target found!");
+				break;
+			}
+			else if(arr[mid]<target) {
+                // which means target is to the right of mid element
+				low=mid+1;
+			}
+			else {
+                //target is to the left of mid element
+				high=mid-1;
+			}
+			
+		}
+
+		if(flag==0) {
+			System.out.println("Target not found!");
+		}
+```
+
+In this algorithm, the searching interval of the array is divided into half at every iteration until the target is found. This results in lesser comparisions and decreases the time required.
+
+## Time complexity:
+
+Linear/Sequential search: O(n)<br />
+Binary search : O(log n)
+
+## Points to Remember:
+
+- Binary search requires a sorted array.
+- Works for 1 dimensional arrays.
+- Faster and complex than sequential search.
+- Uses the divide and conquer approach.
+- Best if arrays are too long (large datasets).