Consider slender body of length  and typical diameter  with , surrounded by fluid of viscosity  whose motion is governed by the Stokes equations. Note that the Stokes' paradox implies that the limit of infinite aspect ratio  is singular, as no Stokes flow can exist around an infinite cylinder.
Slender-body theory allows us to derive an approximate relationship between the velocity of the body at each point along its length and the force per unit length experienced by the body at that point.
Let the axis of the body be described by , where  is an arc-length coordinate, and  is time. By virtue of the slenderness of the body, the force exerted on the fluid at the surface of the body may be approximated by a distribution of Stokeslets along the axis with force density  per unit length.  is assumed to vary only over lengths much greater than , and the fluid velocity at the surface adjacent to  is well-approximated by .
The fluid velocity  at a general point  due to such a distribution can be written in terms of an integral of the Oseen tensor (named after Carl Wilhelm Oseen), which acts as a Greens function for a single Stokeslet. We have
where  is the identity tensor.
Asymptotic analysis can then be used to show that the leading-order contribution to the integral for a point  on the surface of the body adjacent to position  comes from the force distribution at . Since , we approximate . We then obtain
where .
The expression may be inverted to give the force density in terms of the motion of the body:
Two canonical results that follow immediately are for the drag force  on a rigid cylinder (length , radius ) moving a velocity  either parallel to its axis or perpendicular to it. The parallel case gives
while the perpendicular case gives
with only a factor of two difference.
Note that the dominant length scale in the above expressions is the longer length ; the shorter length has only a weak effect through the logarithm of the aspect ratio. In slender-body theory results, there are  corrections to the logarithm, so even for relatively large values of  the error terms will not be that small.