The value of indexes is in speeding reads. For instance, if you are doing lots of SELECTs based on a range of dates in a date column, it makes sense to put an index on that column. And of course, generally you add indexes on any column you're going to be JOINing on with any significant frequency. The efficiency gain is also related to the ratio of the size of your typical recordsets to the number of records (i.e. grabbing 20/2000 records benefits more from indexing than grabbing 90/100 records). A lookup on an unindexed column is essentially a linear search.
The cost of indexes comes on writes, because every INSERT also requires an internal insert to each column index.
So, the answer depends entirely on your application -- if it's something like a dynamic website where the number of reads can be 100x or 1000x the writes, and you're doing frequent, disparate lookups based on data columns, indexing may well be beneficial. But if writes greatly outnumber reads, then your tuning should focus on speeding those queries.
It takes very little time to identify and benchmark a handful of your app's most frequent operations both with and without indexes on the JOIN/WHERE columns, I suggest you do that. It's also smart to monitor your production app and identify the most expensive, and most frequent queries, and focus your optimization efforts on the intersection of those two sets of queries (which could mean indexes or something totally different, like allocating more or less memory for query or join caches).
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