diff --git a/FirstndLast.py b/FirstndLast.py
new file mode 100644
index 00000000..58d9dc08
--- /dev/null
+++ b/FirstndLast.py
@@ -0,0 +1,42 @@
+# Time Complexity : O(log n)
+# Space Complexity : O(1)
+# Did this code successfully run on Leetcode : Yes
+# Any problem you faced while coding this : No
+# Approach: Use two binary searches. The first binary search finds the first occurrence and 
+# The second binary search finds the last occurrence
+
+class Solution:
+    def searchRange(self, nums: List[int], target: int) -> List[int]:
+
+        def findFirst(l, h):
+            while l <= h:
+                m = (l + h) // 2
+                if nums[m] == target:
+                    if m == 0 or nums[m - 1] != target:
+                        return m
+                    h = m - 1
+                elif nums[m] < target:
+                    l = m + 1
+                else:
+                    h = m - 1
+            return -1
+        
+        def findSecond(l, h):
+            while l <= h:
+                m = (l + h) // 2
+                if nums[m] == target:
+                    if m == len(nums) - 1 or nums[m + 1] != target:
+                        return m
+                    l = m + 1
+                elif nums[m] > target:
+                    h = m - 1
+                else:
+                    l = m + 1
+            return -1
+        
+        first = findFirst(0, len(nums) - 1)
+        if first == -1:
+            return [-1, -1]
+        
+        second = findSecond(first, len(nums) - 1)
+        return [first, second]
diff --git a/findMin.py b/findMin.py
new file mode 100644
index 00000000..ce09befa
--- /dev/null
+++ b/findMin.py
@@ -0,0 +1,23 @@
+# Time Complexity : O(log n)
+# Space Complexity : O(1)
+# Did this code successfully run on Leetcode : Yes
+# Any problem you faced while coding this : No
+# Approach: Use binary search on the rotated sorted array and 
+# Track the minimum value while narrowing the search space.
+
+class Solution:
+    def findMin(self, nums: List[int]) -> int:
+        l = 0
+        h = len(nums) - 1
+        res = float('inf')
+
+        while l <= h:
+            m = (l + h) // 2
+            res = min(res, nums[m])
+
+            if nums[m] > nums[h]:
+                l = m + 1
+            else:
+                h = m - 1
+
+        return res
diff --git a/findpeak.py b/findpeak.py
new file mode 100644
index 00000000..6b05e5f7
--- /dev/null
+++ b/findpeak.py
@@ -0,0 +1,22 @@
+# Time Complexity : O(log n)
+# Space Complexity : O(1)
+# Did this code successfully run on Leetcode : Yes
+# Any problem you faced while coding this : No
+# Approach:
+# Use binary search to find a peak element. A peak element is greater than its neighbors.
+# Narrow the search space until a peak is found.
+
+class Solution:
+    def findPeakElement(self, nums: List[int]) -> int:
+        l = 0
+        h = len(nums) - 1
+        while l <= h:
+            m = (l + h) // 2
+            if (m == 0 or nums[m - 1] < nums[m])  and (m == len(nums) - 1 or nums[m] > nums[m + 1]):
+                return m 
+            elif nums[m + 1] > nums[m]:
+                l = m + 1
+            else:
+                h = m - 1
+        
+        return -1