diff --git a/README.md b/README.md
index 6aec9a2..0bb5d95 100644
--- a/README.md
+++ b/README.md
@@ -187,6 +187,7 @@ Useful for preparing for technical interviews and improving your SQL skills.
     - [3421. Find Students Who Improved](./leetcode/medium/3421.%20Find%20Students%20Who%20Improved.sql)
     - [3475. DNA Pattern Recognition](./leetcode/medium/3475.%20DNA%20Pattern%20Recognition.sql)
     - [3497. Analyze Subscription Conversion](./leetcode/medium/3497.%20Analyze%20Subscription%20Conversion.sql)
+    - [3521. Find Product Recommendation Pairs](./leetcode/medium/3521.%20Find%20Product%20Recommendation%20Pairs.sql)
     - [3564. Seasonal Sales Analysis](./leetcode/medium/3564.%20Seasonal%20Sales%20Analysis.sql)
     - [3601. Find Drivers with Improved Fuel Efficiency](./leetcode/medium/3601.%20Find%20Drivers%20with%20Improved%20Fuel%20Efficiency.sql)
 3. [Hard](./leetcode/hard/)
diff --git a/leetcode/medium/3521. Find Product Recommendation Pairs.sql b/leetcode/medium/3521. Find Product Recommendation Pairs.sql
new file mode 100644
index 0000000..bda4396
--- /dev/null
+++ b/leetcode/medium/3521. Find Product Recommendation Pairs.sql	
@@ -0,0 +1,53 @@
+/*
+Question 3521. Find Product Recommendation Pairs
+Link: https://leetcode.com/problems/find-product-recommendation-pairs/description/?envType=problem-list-v2&envId=database
+
+Table: ProductPurchases
+
++-------------+------+
+| Column Name | Type | 
++-------------+------+
+| user_id     | int  |
+| product_id  | int  |
+| quantity    | int  |
++-------------+------+
+(user_id, product_id) is the unique key for this table.
+Each row represents a purchase of a product by a user in a specific quantity.
+Table: ProductInfo
+
++-------------+---------+
+| Column Name | Type    | 
++-------------+---------+
+| product_id  | int     |
+| category    | varchar |
+| price       | decimal |
++-------------+---------+
+product_id is the primary key for this table.
+Each row assigns a category and price to a product.
+Amazon wants to implement the Customers who bought this also bought... feature based on co-purchase patterns. Write a solution to :
+
+Identify distinct product pairs frequently purchased together by the same customers (where product1_id < product2_id)
+For each product pair, determine how many customers purchased both products
+A product pair is considered for recommendation if at least 3 different customers have purchased both products.
+
+Return the result table ordered by customer_count in descending order, and in case of a tie, by product1_id in ascending order, and then by product2_id in ascending order.
+*/
+
+SELECT 
+    p1.product_id AS product1_id,
+    p2.product_id AS product2_id,
+    p1.category AS product1_category,
+    p2.category AS product2_category,
+    COUNT(DISTINCT pp1.user_id) AS customer_count
+FROM ProductInfo AS p1
+CROSS JOIN ProductInfo AS p2
+RIGHT JOIN --noqa: CV08
+    ProductPurchases AS pp1
+    ON p1.product_id = pp1.product_id
+RIGHT JOIN --noqa: CV08
+    ProductPurchases AS pp2
+    ON p2.product_id = pp2.product_id AND pp1.user_id = pp2.user_id
+WHERE p1.product_id < p2.product_id
+GROUP BY p1.product_id, p2.product_id, p1.category, p2.category
+HAVING COUNT(DISTINCT pp1.user_id) >= 3 AND COUNT(DISTINCT pp2.user_id) >= 3
+ORDER BY customer_count DESC, p1.product_id ASC, p2.product_id ASC