K&N Select Oil Filter: Designed to Protect your Engine: Fits Select DODGE /CHRYSLER /JEEP /MITSUBISHI Vehicle Models (See Product Description for Full List of Compatible Vehicles), SO-2004 (Pack of 6)
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You can check the price history of K&N Select Oil Filter: Designed to Protect your Engine: Fits Select DODGE /CHRYSLER /JEEP /MITSUBISHI Vehicle Models (See Product Description for Full List of Compatible Vehicles), SO-2004 (Pack of 6) here. This product's current Price in USA is $65.94. The average and highest prices are $65.94 and $65.94 respectively. The current offer price of the product is $72.93.
Lowest Ever Price
$65.94
25th Jul 2026
Average Price
$65.94
Based on 27 days price tracking
Highest Price
$65.94
25th Jul 2026
Current Price in USA
Price
$65.94
Product Information
Details
Product Name
K&N Select Oil Filter: Designed to Protect your Engine: Fits Select DODGE /CHRYSLER /JEEP /MITSUBISHI Vehicle Models (See Product Description for Full List of Compatible Vehicles), SO-2004 (Pack of 6)
Store Product Code
B0FD81XFZT
Store Name
amazon.com
Brand
K&N
Rating
9 / 10
Category
Oil Filters
Product Manufacturer
K&N Engineering, Inc.
Model Number
SO-2004
Features
The information below is per-pack only
LONG LIFE DESIGN: Up to 20,000 mile engine protection. Follow your manufacturers change intervals
HIGH FILTERATION EFFICIENCY: Captures 99% of contaminate greater than 30 micron
VERSATILE COMPATIBILITY: Designed to operate with all synthetic oil, conventional oil, high mileage and synthetic blended motor oils
PROTECT YOUR ENGINE: Pleated synthetic-blend filtration media removes most harmful contaminants
PREMIUM PERFORMANCE: Laboratory tested to ensure excellent filtration and premium quality
Images
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Rating and Reviews
9Based on 263 reviews
KN Select Oil Filter Designed to Protect has 9 rating out of 10. This average rating is consist of 263 individual ratings. You can rate this product at product review page.
* Predictions is created on based of past prices and trends, it does not guarantee that it will happen. These are just prediction for theoretical information only.