  {The determination of cluster masses is a complex problem that would be aided
by information about the cluster shape and orientation (along the
line-of-sight).} {It is in this context, that we have developed a scheme for
identifying the intrinsic morphology and inclination of a cluster, by looking
for the signature of the true cluster characteristics in the inter-comparison
of the different deprojected emissivity profiles (that all project to the same
X-ray brightness distribution) and by using SZe data when available.} {We
deproject the cluster X-ray surface brightness profile under the assumptions of
four different geometry and inclination configurations for the observed system;
these 4 configurations correspond to four extreme geometry+inclination
scenarios. The deprojection in question is performed by the non-parametric
algorithm DOPING. The formalism is tested with model systems and then is
applied to a sample of 24 clusters. While the shape determination is possible
by implementing the X-ray brightness alone, the estimation of the inclination
is usually markedly improved by the usage of SZe data that is available for the
considered sample.}{We spot 8 prolate systems, 1 oblate and 15 of the clusters
in our sample as triaxial. In fact, for systems identified as triaxial, we are
able to discern how the three semi-axes lengths compare with each other. This,
when compounded by the information about the line-of-sight extent, allows us to
constrain the inclination quite tightly and offers the two intrinsic axial
ratios of the triaxial systems.}{}
